View in EDS HTML Full Text PDF Full Text

Do Schools That Employ an Inspector Get Better Inspection Grades?

Saved in:
Bibliographic Details
Title: Do Schools That Employ an Inspector Get Better Inspection Grades?
Language: English
Authors: Christian Bokhove (ORCID 0000-0002-4860-8723), John Jerrim, Sam Sims
Source: British Educational Research Journal. 2024 50(5):2383-2406.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 24
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Foreign Countries, Inspection, Institutional Evaluation, Leaders, School Administration, Employment
Geographic Terms: United Kingdom (England)
DOI: 10.1002/berj.4025
ISSN: 0141-1926
1469-3518
Abstract: In England, a substantial proportion of school inspections are conducted by current school leaders. This may lead to concerns that this gives their school (about 2% of schools) an advantage in the inspection process when it is their turn to be inspected. Yet scant evidence exists on this issue. This paper thus presents the first evidence on this matter, using data obtained via a freedom of information request and linking this with other publicly available information about England's schools. We find that schools where a member of staff also works for Ofsted receive better inspection outcomes than schools without an inspector on their payroll. Our findings nevertheless suggest that other schools may benefit from having access to the training material and professional development opportunities Ofsted provides to its inspectors.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1442252
Database: ERIC
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
    Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwFP9an4mDgy7e8XwC2zUSeVAAAA4zCB4AYJKoZIhvcNAQcGoIHSMIHPAgEAMIHJBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDM-Nipf_XfIou0QNJwIBEICBm5VRksWl8GteYnXIqOtH5X_WYM6in8aHgS4u3isS1C4DPtzYF4CKQM1R-21yD_nXsrOlPooB07UIWyJBvhte_jOvs85lfnp8PD76ECtmrQeAvJSzTxj8nRwRz5rt-R7BWzvFz89XMLcAf0wJ7zp-JRQVliRWUKmPlS8_9s8czej-wPIh0sBCPjQpBrG4OuYp8SyIZ-ObguV20O4H
Text:
  Availability: 1
  Value: <anid>AN0180149881;bed01oct.24;2024Oct10.03:58;v2.2.500</anid> <title id="AN0180149881-1">Do schools that employ an inspector get better inspection grades? </title> <p>In England, a substantial proportion of school inspections are conducted by current school leaders. This may lead to concerns that this gives their school (about 2% of schools) an advantage in the inspection process when it is their turn to be inspected. Yet scant evidence exists on this issue. This paper thus presents the first evidence on this matter, using data obtained via a freedom of information request and linking this with other publicly available information about England's schools. We find that schools where a member of staff also works for Ofsted receive better inspection outcomes than schools without an inspector on their payroll. Our findings nevertheless suggest that other schools may benefit from having access to the training material and professional development opportunities Ofsted provides to its inspectors.</p> <p>Keywords: consistency; Ofsted; reliability; school inspections</p> <hd id="AN0180149881-2">Key insights</hd> <p></p> <hd id="AN0180149881-3">What is the main issue that the paper addresses?</hd> <p>The paper explores whether schools that employ a school inspector receive better inspection grades.</p> <hd id="AN0180149881-4">What are the main insights that the paper provides?</hd> <p>The paper provides the first evidence that schools that employ a school inspector do indeed receive better inspection grades. We speculate about four broad mechanisms that are likely to drive this association.</p> <hd id="AN0180149881-5">INTRODUCTION</hd> <p>Education systems in all countries are governed by a system of accountability. However, how such accountability systems are structured varies in several important ways. Some countries, such as England and the United States, have a system of high‐stakes accountability, making extensive use of data on matters such as pupil attendance and test scores. Such systems are based upon the presumption that the monitoring and publication of such information will help ensure minimum educational standards are met and provide a strong incentive for schools to improve. Continental Europe, on the other hand, has traditionally had a model of lower‐stakes accountability, where the primary purpose is to 'foster reflexive thinking by teachers' and aim 'to make teachers more aware of the value of their teaching methods' (Barbana et al., [<reflink idref="bib2" id="ref1">2</reflink>], p. 89). Thus, while these different approaches to accountability have a shared goal—to lead to school improvement—they attempt to achieve it in rather different ways.</p> <p>School inspections are a prominent part of education system accountability in many countries (OECD, [<reflink idref="bib17" id="ref2">17</reflink>]). Proponents argue that these inspections help raise education standards, while also ensuring children remain safe and secure when at school (Jones & Tymms, [<reflink idref="bib14" id="ref3">14</reflink>]). Those that argue against high‐stakes school inspections highlight the negative impacts of their unintended consequences, including the impact they have on teacher workload, wellbeing and retention in the teaching profession (de Wolfe & Janssens, [<reflink idref="bib10" id="ref4">10</reflink>]; Ehren et al., [<reflink idref="bib11" id="ref5">11</reflink>]; Perryman, [<reflink idref="bib26" id="ref6">26</reflink>]; Perryman et al., [<reflink idref="bib27" id="ref7">27</reflink>]). School inspections come in many shapes and sizes, with different consequences attached to the results. England is known for its high‐stakes inspection regime (Ehren et al., [<reflink idref="bib12" id="ref8">12</reflink>]). Schools are awarded a grade based upon the judgements of its inspectors, following the criteria set in the latest inspection framework. These get widely reported by local media and used by parents when they are choosing schools (Bokhove et al., [<reflink idref="bib4" id="ref9">4</reflink>]). Receipt of a low rating can have serious consequences, leading to a change to the school management structure (e.g., a requirement to join an academy chain) or the headteacher losing their job (Eyles & Machin, [<reflink idref="bib13" id="ref10">13</reflink>]).</p> <p>When the outcomes of inspections are high stakes, issues surrounding their consistency, reliability and validity are key. If, for instance, two otherwise identical schools are awarded a different inspection grade, then this leads to questions surrounding the results. Unfortunately, the international evidence on this important issue remains sparse, particularly in terms of quantitative analyses conducted by independent research teams.</p> <p>In this paper, we explore one specific element within the broader literature on inspection consistency—whether schools that have some inside knowledge of the inspection process are awarded more favourable inspection judgements. An important feature of Ofsted's inspections is that a substantial proportion are conducted by existing school leaders or other members of senior school staff (Moreton et al., [<reflink idref="bib16" id="ref11">16</reflink>]). Such inspections are hence essentially a form of peer review. While this approach has many potential benefits, especially in the form of understanding what the role of teacher or school leader entails, it also brings certain challenges. One is that these individuals—and the schools in which they work—may gain an advantage in the inspection process. If true—and depending on what is driving it—this raises important questions surrounding equity and fairness in the inspection process. To our knowledge, there is no existing evidence on this issue, either in England or internationally. It is this gap in the literature that this paper starts to fill.</p> <hd id="AN0180149881-6">Background context—a brief overview of school inspections in England</hd> <p>Schools in England are routinely inspected by Ofsted roughly every 4 to 5 years. A team of trained inspectors visit the school and make judgements about four different aspects of its provision (quality of education, behaviour and attitudes, personal development, leadership and management), along with its overall effectiveness and the adequacy of its safeguarding arrangements. These inspectors work together in regional teams. The criteria schools are inspected under are set out in the inspection handbook, with a major revision to Ofsted's inspection framework taking place in 2019 (Office for Standards in Education, [<reflink idref="bib22" id="ref12">22</reflink>]). This placed much less emphasis on school performance measures and other data, and more upon the quality of a school's curriculum. Owing to inspections being paused during the COVID‐19 pandemic, most of the schools inspected during the 2022/23 academic year were being judged according to this new framework for the first time. The consequences of these inspections can be high stakes for schools, with the results being widely reported in local media and often used by parents when they are choosing a school (Bokhove et al., [<reflink idref="bib4" id="ref13">4</reflink>]). At the extreme, an Inadequate rating can lead to the headteacher losing their job (Ehren et al., [<reflink idref="bib12" id="ref14">12</reflink>]).</p> <p>The Ofsted inspectors who conduct the inspections are trained in the inspection framework. As mentioned before, inspectors fall into one of two groups in terms of their employment contract with Ofsted: His Majesty's Inspectors (HMIs) as permanent members of Ofsted staff for whom Ofsted is their sole employer and Ofsted Inspectors (OIs) conducting school inspections on behalf of Ofsted on a freelance basis (Office for Standards in Education, [<reflink idref="bib23" id="ref15">23</reflink>]). Many OIs are working as teachers or senior leaders in schools, with this being their main form of employment. Hence, for most OIs, the inspections they conduct for Ofsted represent a minor source of income for their school (at the time of writing, their school is paid between £335 and £535 for each day of inspection work). Inspections conducted by these inspectors are hence essentially a form of peer review, where senior staff from one school make judgements about another school. Our primary interest is how their <emph>own school</emph> performs when it is inspected by Ofsted.</p> <hd id="AN0180149881-7">Why might inside knowledge help schools to achieve a better inspection outcome?</hd> <p>Throughout this paper, we operationalise access to 'inside knowledge' as a school having at least one member of staff who also works for Ofsted—conducting inspections on a freelance basis. As part of this role, these individuals receive extensive training in how to conduct inspections. This includes judging the provision provided by schools according to Ofsted's inspection framework, as set out in its inspection handbook (Office for Standards in Education, [<reflink idref="bib22" id="ref16">22</reflink>]). As part of this role, they will have access to material not in the public domain, as well as bespoke professional development opportunities. They also become part of a professional network, meeting, training and working with other Ofsted inspectors in the same region.</p> <p>We suggest four possible reasons why this may then lead to the school in which these individuals work (e.g., as a school leader) receiving better inspection outcomes.</p> <p>First, Human Capital Theory (Becker, [<reflink idref="bib3" id="ref17">3</reflink>]), from the economics literature, suggests that when an individual receives training in an area, their knowledge and skills will improve, making them a more efficient and effective employee. This would suggest that the extensive training required to become an inspector—and seeing both good and bad practice elsewhere—may mean these individuals become better leaders and introduce more effective practices within their own school. The advantage they gain is hence through a boost to their 'human capital' (i.e., their knowledge and skills), which they convert into more effective instructional practice in the school they work in.</p> <p>An alternative theory from economics—that often runs counter to Becker's notion of training improving human capital—is that of signalling (Stiglitz, [<reflink idref="bib29" id="ref18">29</reflink>]). This postulates that, rather than training and experience boosting an individual's skills, it simply helps them to send implicit signals of their quality. In our application, this 'signalling' could be helping headteachers who train as inspectors to know what inspectors look for during inspections, ensuring they tick the right boxes. Rather than genuinely improving the quality of their school, they become better at 'window‐dressing' (i.e., sending the right signals), including knowing what to say (and what not to say) when the inspection takes place. They may also be able to devote their efforts and resources to specific areas they know inspectors will look at during the inspection process (even if this is of limited material benefit for learners at the school). Or, as put by one former inspector: 'schools with inspectors felt they had an advantage because they know what Ofsted's looking for' (Walker, [<reflink idref="bib34" id="ref19">34</reflink>]).</p> <p>Third, any apparent advantage could be due to a selection effect. For instance, Ofsted may only employ the best, most effective leaders as inspectors; those who are particularly adept at improving learning and instruction in schools (with or without the training and experience they gain through working as an inspector). Relatedly, the pool of serving inspectors may be disproportionately drawn from certain types of school (e.g., those of higher quality) which—if unaccounted for—could confound the results.</p> <p>Finally, by becoming an inspector, the individual becomes a member of a professional network. They will train, work and potentially even socialise with other Ofsted inspectors. This could include those individuals who end up inspecting their schools. Although Ofsted has strict conflict of interest policies in place (Office for Standards in Education, [<reflink idref="bib24" id="ref20">24</reflink>]), it seems reasonable to assume that individuals who work as an Ofsted inspector may be more likely to know (or at least be an acquaintance of) a member of the team that inspects their school. Theoretical research from economics has discussed the role that such professional networks can play in employment decisions, giving some individuals an unfair advantage in the recruitment process (Ponzo & Scoppa, [<reflink idref="bib28" id="ref21">28</reflink>]). The aforementioned work notes how professional networks may play a stronger role in recruitment decisions when the skills of workers are not verifiable and when the evaluation of their skills is subjective. As school inspection judgements are also subjective—capturing the views and opinions formed by inspection teams—they may also be susceptible to similar professional network effects. Indeed, such professional network effects could be particularly strong in a school inspection context, given that when one headteacher inspects the school of another headteacher who also works as an inspector, they understand that one day the boot could be on the other foot.</p> <hd id="AN0180149881-8">Policy/sector interest</hd> <p>The topic of this paper has become an issue across the education sector in England. A relatively recent example comes from October 2022, when a selection of Ofsted's training materials was leaked online (Walker, [<reflink idref="bib33" id="ref22">33</reflink>]). This information was previously only available to those working as Ofsted inspectors, illustrating the type of 'inside knowledge' these individuals have access to. The Association for School and College Leaders (ASCL) has since argued that some of the materials now circulating are either erroneous or out‐of‐date, expressing disappointment that updated versions—and Ofsted's other training material—has not since been more broadly released by the school inspectorate (ASCL, [<reflink idref="bib1" id="ref23">1</reflink>]). They argued that 'While Ofsted continues to employ serving school leaders as OIs [Ofsted Inspectors], we strongly believe that recordings of OI training and the associated materials should be in the public domain, available for all school leaders and teachers to access. This would be significantly more transparent and equitable' (UK Parliament, [<reflink idref="bib31" id="ref24">31</reflink>]).</p> <p>It also seems that the importance of this issue is likely to increase further. In January 2024, Martyn Oliver is due to take over from Amanda Spielman as His Majesty's Chief Inspector (HMCI). When applying for the role, Oliver expressed his intention to increase the number of school leaders working as inspectors, stating 'the problems now facing the validity of [inspection] judgments can be overcome by creating an OFSTED workforce consisting of far more current serving leaders. This would be a key priority for me' (UK Parliament, [<reflink idref="bib32" id="ref25">32</reflink>]). While this approach may have benefits, it also has implications for how and where inside knowledge of the inspection process flows through the education system. Its pros and cons to a large extent depend upon which of the aforementioned mechanisms are at play. If training and working as an inspector boosts leaders' human capital, then this approach may help raise standards across the education sector. But, if the other mechanisms are at work, then such an approach could end up doing more harm than good.</p> <hd id="AN0180149881-9">Previous research</hd> <p>The issue can be seen as part of the broader literature surrounding the consistency and reliability of school inspection. An extensive qualitative literature has found school inspections to be subject to subjectivity, emotions and trust, especially because of strategic behaviour by schools. For example, Tian ([<reflink idref="bib30" id="ref26">30</reflink>]) interviewed headteachers about their inspection experiences, finding that they employed micropolitical strategies in response to the introduction of the Education Inspection Framework in 2019. In other cases, school leaders and management made decisions to conform to Ofsted's expectations, to some extent 'performing' as a good school (Perryman et al., [<reflink idref="bib27" id="ref27">27</reflink>]). Unintended consequences of school inspections—often due to such strategic behaviour—have also been widely covered in this literature, including narrowing educational practices, increased workloads and the associated stress that this entails (Ehren et al., [<reflink idref="bib12" id="ref28">12</reflink>]). It has also led headteachers to focus more on pupils' attainment and progress, as they experience that inspections are often focused on these factors (Courtney, [<reflink idref="bib8" id="ref29">8</reflink>]). Even when broadly agreeing with framework principles underpinning inspections, some headteachers report having negative experiences of the process due to variation in inspector quality and the rigidity with which inspection frameworks are interpreted (Courtney, [<reflink idref="bib8" id="ref30">8</reflink>]). Furthermore, the experience of having to constantly be visible, the pressure of performing to shifting expectations and challenges of staffing instability can actually work against school improvement (Colman, [<reflink idref="bib7" id="ref31">7</reflink>])—particularly in areas of deprivation. Others have argued that particular ideologies are deeply embedded in Ofsted as an organisation (e.g., Cushing & Snell, [<reflink idref="bib9" id="ref32">9</reflink>]) and that the inspectorate plays a key role in teacher surveillance (Page, [<reflink idref="bib25" id="ref33">25</reflink>]).</p> <p>As noted elsewhere, independent quantitative research in this area remains relatively sparse, both within England and internationally. Indeed, much previous work into issues surrounding inspection reliability and consistency has been conducted by school inspectorates themselves. Ofsted in England has conducted such research sporadically since its inception in the 1990s. In one of the first studies, Matthews et al. ([<reflink idref="bib15" id="ref34">15</reflink>]) reported there to be moderate levels of inter‐rater reliability across the gradings awarded by two independent inspectors. This was followed in 2017 by a study investigating the consistency of judgements made by inspectors conducting their ungraded inspections (Office for Standards in Education, [<reflink idref="bib18" id="ref35">18</reflink>]). The results from that study reported a high degree of consistency. They have also investigated how reliably inspectors can complete certain inspection tasks. This includes scrutiny of pupils' work and lesson observations, where different inspectors provided independent judgements, reporting moderate levels of inter‐rater reliability (Office for Standards in Education, [<reflink idref="bib19" id="ref36">19</reflink>], [<reflink idref="bib20" id="ref37">20</reflink>]). There are, on the other hand, very few existing studies conducted by independent research teams. Bokhove et al. ([<reflink idref="bib5" id="ref38">5</reflink>]) is a notable recent exception, examining how inspection judgements are related to the characteristics of the lead inspector. They find a small difference in judgements in relation to inspector gender, but a more substantial difference between HMIs and OIs.</p> <hd id="AN0180149881-10">The present study</hd> <p>Although the aforementioned literature has made an important contribution to our collective understanding of school inspections, key gaps in the evidence base remain. No existing study has investigated how having inside knowledge of the inspection process (i.e., having a member of staff who also works as a school inspector) is related to inspection outcomes. We thus contribute novel insights into this issue by addressing two research questions.</p> <p>To begin, we investigate the prevalence and distribution of access to such inside knowledge across schools in England. In particular, we investigate how many schools that were inspected during the 2022/23 academic year had a member of staff on the Ofsted payroll, and how this varies by school characteristics (e.g., prior Ofsted rating, proportion of disadvantaged pupils). Our first research question is as follows.</p> <p></p> <ulist> <item> <emph>RQ1: How many schools inspected in the 2022/23 academic year had a member of staff conducting inspections on behalf of Ofsted? How did this vary across school characteristics?</emph> </item> </ulist> <p>We then turn to the link between access to inside knowledge and inspection outcomes. Do schools with an Ofsted inspector on their payroll get awarded more favourable inspection judgements? Our analysis presents the first evidence on this issue by asking the second research question as follows.</p> <p></p> <ulist> <item> <emph>RQ2: Do schools with a staff member who is also employed by Ofsted receive better inspection outcomes?</emph> </item> </ulist> <hd id="AN0180149881-11">DATA AND METHODOLOGY</hd> <p></p> <hd id="AN0180149881-12">Data</hd> <p>The data we use were released by Ofsted to journalists from the publication <emph>Schools Week</emph> (Walker, [<reflink idref="bib34" id="ref39">34</reflink>]) following a freedom of information request. The file contained a list of the school, trust or council where 762 of Ofsted's OIs work. The file was accurate as of October 2022, thus capturing those schools that had at least one member of staff conducting inspections on behalf of Ofsted during the 2022/23 academic year. The journalists that obtained the data went through the file they received and merged in some key information about the institution from external sources (e.g., school URN).[<reflink idref="bib1" id="ref40">1</reflink>] We contacted the journalists when we first became aware of the data in September 2023, and they agreed to share it with us to conduct this research. Appendix A provides details about how we have checked the reliability of these data.</p> <p>From Ofsted's routinely published information (https://<ulink href="http://www.gov.uk/government/statistical‐data‐sets/monthly‐management‐information‐ofsteds‐school‐inspections‐outcomes),">www.gov.uk/government/statistical‐data‐sets/monthly‐management‐information‐ofsteds‐school‐inspections‐outcomes),</ulink> we downloaded information on all inspections that were conducted during the 2022/23 academic year. Of these, 150 were conducted at a school that had 'inside knowledge'—defined as where at least one member of staff was also serving as an Ofsted inspector. This represents just 2.4% of all inspections conducted and hence only impacts a small proportion of Ofsted's work.</p> <p>Further information has then been added to this data file from other publicly available sources. This includes information on school inspection outcomes, measures of performance in national examinations and recent levels of pupil absence. The key measures we used are as follows.</p> <p></p> <ulist> <item> <emph>Graded school inspection outcomes</emph>. Ofsted conducts two broad forms of inspection—graded and ungraded. For graded inspections, schools receive one of four overall effectiveness judgements (Outstanding, Good, Requires Improvement and Inadequate), along with sub‐judgements in four areas. We combine the bottom two categories (Requires Improvement and Inadequate) in our analysis to avoid small cell sizes (only 4% of schools receive an Inadequate grade). Information is also available on the overall effectiveness grade the school was awarded in its most recent prior inspection.</item> <p></p> <item> <emph>Inside knowledge</emph>. Inside knowledge in this paper is operationalised as a school having at least one member of staff who was also working for Ofsted as an OI in October 2022. This is a dummy variable in our dataset, coded 1 if the school has such a member of staff, and 0 otherwise.</item> <p></p> <item> <emph>Ungraded school inspections</emph>. These inspections are conducted by a smaller team and are reserved for schools that were previously rated Outstanding or Good. For schools rated as Good in their previous inspection (the majority of ungraded inspections) there are four possible outcomes: (a) signs of potential improvement; (b) no change and remains Good; (c) signs of potential decline; (d) immediate conversion to full inspection due to serious concerns. Our focus is on the first three of these outcomes, as the fourth (immediate conversion) is exceptionally rare (only around 1% of short inspections were immediately converted during the 2022/23 academic year).</item> <p></p> <item> <emph>School performance</emph>. Information on school performance in national examinations has been extracted from the school performance tables. For primary schools, this is based upon results from 2019 SATS tests, averaged across reading, grammar/punctuation/spelling and mathematics. [<reflink idref="bib2" id="ref41">2</reflink>] For secondary schools, the measure is based upon Attainment 8 outcomes in 2022, although we have tested the robustness of our findings to using Progress 8 instead (leading to little change to our substantive results). For both primary and secondary schools, we standardised these attainment measures to mean 0 and standard deviation 1 across all state schools in England.</item> <p></p> <item> <emph>Absences</emph>. Information on school absences is drawn from information within the school performance tables with respect to the 2021/22 academic year. It includes both the percentage of total absences and the percentage of pupils classed as persistently absent (missing more than 10% of sessions in total).</item> </ulist> <hd id="AN0180149881-13">Methodology</hd> <p>Our analysis begins by presenting a simple cross‐tabulation between overall effectiveness grade and whether the school has an OI on their payroll. This provides a first descriptive overview of the link between a school having access to inside knowledge and inspection outcomes.</p> <p>One issue with these estimates is that they may be subject to confounding. As we will illustrate when answering RQ1, schools with particular characteristics (selective intakes, Good/Outstanding prior inspection ratings) are more likely to be employing an OI. We thus proceed by controlling for a set of school background characteristics that could potentially confound the unconditional results. These ordinal logistic regression models are of the form1 <ephtml> <math altimg="urn:x-wiley:01411926:media:berj4025:berj4025-math-0001" display="block" overflow="scroll" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>log</mi><mfenced close=")" open="("><mfrac><mrow><mi>P</mi><mfenced close=")" open="("><mrow><msub><mi>O</mi><mi>i</mi></msub><mo>≤</mo><mi>k</mi></mrow></mfenced></mrow><mrow><mi>P</mi><mfenced close=")" open="("><mrow><msub><mi>O</mi><mi>i</mi></msub><mo>></mo><mi>k</mi></mrow></mfenced></mrow></mfrac></mfenced><mo linebreak="goodbreak">=</mo><msub><mi>α</mi><mi>k</mi></msub><mo linebreak="goodbreak">+</mo><mi>β</mi><msub><mi mathvariant="italic">IK</mi><mi>i</mi></msub><mo linebreak="goodbreak">+</mo><mi>τ</mi><msub><mi>B</mi><mi>i</mi></msub><mo linebreak="goodbreak">+</mo><mi>ϕ</mi><msub><mtext mathvariant="italic">IDACI</mtext><mi>i</mi></msub><mo linebreak="goodbreak">+</mo><mi>∂</mi><msub><mi mathvariant="italic">ABS</mi><mi>i</mi></msub><mo linebreak="goodbreak">+</mo><mi>θ</mi><msub><mi mathvariant="italic">ACH</mi><mi>i</mi></msub><mo linebreak="goodbreak">+</mo><mi>γ</mi><msub><mi>P</mi><mi>i</mi></msub></mrow></semantics></math> </ephtml></p> <p>where <ephtml> <math altimg="urn:x-wiley:01411926:media:berj4025:berj4025-math-0002" display="inline" overflow="scroll" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>O</mi><mi mathvariant="italic">ij</mi></msub></mrow></semantics></math> </ephtml>  = the overall effectiveness judgement awarded to the school</p> <p> <ephtml> <math altimg="urn:x-wiley:01411926:media:berj4025:berj4025-math-0003" display="inline" overflow="scroll" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi mathvariant="italic">IK</mi><mi>i</mi></msub></mrow></semantics></math> </ephtml>  = a dummy variable indicating whether the school has a member of staff who conducts inspections on behalf of Ofsted (coded 1), and 0 otherwise</p> <p> <ephtml> <math altimg="urn:x-wiley:01411926:media:berj4025:berj4025-math-0004" display="inline" overflow="scroll" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>B</mi><mi>i</mi></msub></mrow></semantics></math> </ephtml>  = a set of background controls about the school, including school phase, inspection type and number of pupils</p> <p> <ephtml> <math altimg="urn:x-wiley:01411926:media:berj4025:berj4025-math-0005" display="inline" overflow="scroll" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mtext mathvariant="italic">IDACI</mtext><mi>i</mi></msub></mrow></semantics></math> </ephtml>  = School Income Deprivation Affecting Children Index (IDACI) quintiles</p> <p> <ephtml> <math altimg="urn:x-wiley:01411926:media:berj4025:berj4025-math-0006" display="inline" overflow="scroll" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi mathvariant="italic">ABS</mi><mi>i</mi></msub></mrow></semantics></math> </ephtml>  = two variables capturing school absence levels (percentage of pupils classed as persistently absent and overall absence rate)</p> <p> <ephtml> <math altimg="urn:x-wiley:01411926:media:berj4025:berj4025-math-0007" display="inline" overflow="scroll" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi mathvariant="italic">ACH</mi><mi>i</mi></msub></mrow></semantics></math> </ephtml>  = the recent performance of schools in Key Stage 2 (primary) or Key Stage 4 (secondary) national examinations</p> <p> <ephtml> <math altimg="urn:x-wiley:01411926:media:berj4025:berj4025-math-0008" display="inline" overflow="scroll" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>P</mi><mi>i</mi></msub></mrow></semantics></math> </ephtml>  = the overall effectiveness rating received by the school during its most recent prior inspection</p> <p>Six different specifications of this model are estimated, with controls sequentially added to establish how this impacts the results. Specification M1 captures the unconditional, bivariate association, with a set of basic school background controls (school phase, inspection type and number of pupils) added in model M2. A measure of school deprivation (IDACI quintile) is included in model M3, with pupil absence levels also controlled in M4. School performance measures (in Key Stage 2 or Key Stage 4 examinations) are added in M5. Our final model (M6) additionally includes the school's Ofsted rating from its most recent previous inspection. We note that there are some potential issues with including this control; schools with 'inside knowledge' in the current inspection may have also had inside knowledge previously (e.g., having a staff member who is also a long‐serving OI, or by consistently encouraging staff to apply to work as an inspector). This could thus arguably be a 'bad control', potentially removing some of the effect we are attempting to estimate (Cinelli et al., [<reflink idref="bib6" id="ref42">6</reflink>]). We nevertheless believe it is important to include this variable in our final specification to investigate whether controlling for prior inspection rating has any impact upon our results.</p> <p>The parameter of interest is <ephtml> <math altimg="urn:x-wiley:01411926:media:berj4025:berj4025-math-0009" display="inline" overflow="scroll" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>β</mi></mrow></semantics></math> </ephtml> . This captures the association between a school having an OI amongst their workforce and their inspection outcome. Estimates are presented as odds ratios, capturing the change in the odds of receiving a <emph>worse</emph> inspection rating. Multiple imputation using chained equations has been used to ensure that observations are not dropped due to missing covariate data.</p> <hd id="AN0180149881-14">Robustness tests</hd> <p>We have tested the robustness of our results in several ways.</p> <p>First, the main outcome we examine is overall effectiveness judgements from graded inspections (the highest‐stakes outcomes). However, as noted above, just under half of all inspections are (short) ungraded inspections. We thus also investigate ungraded inspection judgements for schools that were previously rated as Good as a secondary outcome. These results are presented in the main text below. We do not include ungraded inspections of Outstanding schools because (a) it is not possible for these schools to improve, and hence they would require a different measure, and (b) there were too few previously Outstanding schools that received an ungraded inspection to investigate this group in a separate analysis.[<reflink idref="bib3" id="ref43">3</reflink>] Additionally, we also re‐estimate our models combining information across graded and ungraded inspections to increase the overall sample size[<reflink idref="bib4" id="ref44">4</reflink>] (these results are presented in Appendix C, Tables C1,C2).</p> <p>Second, we re‐estimate the model presented in Equation (<reflink idref="bib1" id="ref45">1</reflink>) using multinomial logistic regression (rather than ordinal logistic regression). This has the advantage of relaxing the proportional odds assumption (whether having inside knowledge is more likely to help a school obtain the top Outstanding grade or is particularly helpful for avoiding a Requires Improvement or Inadequate judgement). These results are presented in the main text below.</p> <p>Third, we expand the sample window to also include inspections conducted during the 2021/22 academic year (in addition to 2022/23). This has both advantages and disadvantages. The main key benefit is that the sample size increases from 6133 to 9882 inspections in total, and from 150 to 221 inspections where the school had an OI on their payroll. The main disadvantage is that the data we hold regarding the schools where inspectors work is correct as of October 2022—after when the 2021/22 academic year inspections took place. When including the 2021/22 academic year inspections in the analysis, we are thus assuming there is a reasonably high degree of inter‐year stability in Ofsted's inspection workforce. These results are presented in Appendix B (Table B1–B5).</p> <hd id="AN0180149881-15">RESULTS</hd> <p></p> <hd id="AN0180149881-16">How many schools inspected in the 2022/23 academic year had a member of staff conducting insp...</hd> <p>To address RQ1, Table 1 illustrates—for schools that were inspected during the 2022/23 academic year—the percentage that had an Ofsted inspector on their payroll, stratified by school characteristics. There are four key points to note.</p> <p>1 TABLE The percentage of inspections conducted in 2022/23 where the school had a staff member working for Ofsted as an inspector.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left" /><th align="left">% Without inside knowledge</th><th>% With inside knowledge</th></tr></thead><tbody valign="top"><tr><td align="left">School type</td><td align="left">PRU</td><td align="left">99</td><td align="char" char=" ">1</td></tr><tr><td align="left">Primary</td><td align="left">99</td><td align="char" char=" ">1</td></tr><tr><td align="left">Secondary</td><td align="left">94</td><td align="char" char=" ">6</td></tr><tr><td align="left">Selective secondary</td><td align="left">85</td><td align="char" char=" ">15</td></tr><tr><td align="left">Special school</td><td align="left">96</td><td align="char" char=" ">4</td></tr><tr><td align="left">Inspection type</td><td align="left">Other (e.g., re‐inspection)</td><td align="left">99</td><td align="char" char=" ">1</td></tr><tr><td align="left">Section 5 inspection</td><td align="left">97</td><td align="char" char=" ">3</td></tr><tr><td align="left">Section 8 inspection</td><td align="left">98</td><td align="char" char=" ">2</td></tr><tr><td align="left">IDACI quintile</td><td align="left">Q1</td><td align="left">97</td><td align="char" char=" ">3</td></tr><tr><td align="left">Q2</td><td align="left">98</td><td align="char" char=" ">2</td></tr><tr><td align="left">Q3</td><td align="left">97</td><td align="char" char=" ">3</td></tr><tr><td align="left">Q4</td><td align="left">98</td><td align="char" char=" ">2</td></tr><tr><td align="left">Q5</td><td align="left">97</td><td align="char" char=" ">3</td></tr><tr><td align="left">Previous rating</td><td align="left">Outstanding</td><td align="left">94</td><td align="char" char=" ">6</td></tr><tr><td align="left">Good</td><td align="left">98</td><td align="char" char=" ">2</td></tr><tr><td align="left">Requires improvement</td><td align="left">99</td><td align="char" char=" ">1</td></tr><tr><td align="left">Inadequate</td><td align="left">99</td><td align="char" char=" ">1</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note</emph>: Estimates based on the 6133 inspections conducted in the 2022/23 academic year. A total of 150 (2.4%) of these inspections involved 'inside knowledge'—that is, whether the school had a staff member who was also an OI. Figures refer to row percentages.</p> <p>First, only a small minority (2.4%) of the schools inspected had an Ofsted inspector on their books. Any advantage that is gained from doing so is hence only of benefit to a small number of schools, representing a minor proportion of Ofsted's overall work.</p> <p>Second, secondary schools were more likely to employ an Ofsted inspector than primary schools (6% vs 1%). This was particularly true for academically selective secondary schools (i.e., grammar schools), where the figure stood at 15% (though we caution that the total number of grammars in the sample is relatively small at 53).[<reflink idref="bib5" id="ref46">5</reflink>]</p> <p>Third, schools previously rated as Outstanding were much more likely to have an inspector as a staff member (6%) than schools with an existing Good (2%), Requires Improvement (1%) or Inadequate (1%) rating. This is likely to reflect Ofsted policy—it is a requirement for serving teachers/leaders applying to become an inspector that their school 'should have been rated as "good" or better at the most recent inspection' (Office for Standards in Education, [<reflink idref="bib21" id="ref47">21</reflink>]).</p> <p>Finally, it is interesting to note that there is little variation according to the socio‐economic intake of the school, as measured by its IDACI quintile. It is thus reassuring that schools serving the most disadvantaged children are equally as likely to have an Ofsted inspector within their ranks.</p> <p>Taken together, these results indicate that any advantage that is gained from having a staff member working for Ofsted is not evenly distributed across the population. Certain types of schools (most notably selective schools and those with a strong prior Ofsted judgement) are disproportionately represented. This also suggests that the raw, unconditional relationship between a school employing an Ofsted inspector and the inspection judgement it receives may to some extent be confounded, depending on where the inspector workforce is drawn from.</p> <hd id="AN0180149881-17">Graded inspections (overall effectiveness judgements)</hd> <p>Table 2 begins by reporting the unconditional association between a school having an inspector on their books and the inspection judgement that it receives. For the moment, we focus on panel (a), which presents the distribution of overall effectiveness judgements from graded inspections.</p> <p>2 TABLE Cross‐tabulation between a school having a staff member working for Ofsted and their inspection outcome.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">% Without inside knowledge</th><th align="left">% With inside knowledge</th></tr></thead><tbody valign="top"><tr><td align="left">(a) Graded (section 5) inspections</td></tr><tr><td align="left">Outstanding</td><td align="left">7%</td><td align="left">20%</td></tr><tr><td align="left">Good</td><td align="left">69%</td><td align="left">71%</td></tr><tr><td align="left">RI/Inadequate</td><td align="left">24%</td><td align="left">8%</td></tr><tr><td align="left">Observations</td><td align="left">3100</td><td align="left">83</td></tr><tr><td align="left">(b) 'Ungraded' (section 8) inspections of previously Good schools</td></tr><tr><td align="left">Potential improvement</td><td align="left">6%</td><td align="left">19%</td></tr><tr><td align="left">Unchanged—remains Good</td><td align="left">80%</td><td align="left">72%</td></tr><tr><td align="left">Concerns</td><td align="left">14%</td><td align="left">9%</td></tr><tr><td align="left">Observations</td><td align="left">2470</td><td align="left">47</td></tr></tbody></table> </ephtml> </p> <p>2 <emph>Note</emph>: Figures refer to column percentages. Panel (b) restricts the sample to schools with a prior rating of Good. The remaining 20 inspections of OI schools not shown in the table are either of previously Outstanding schools (<emph>n</emph> = 16) or re‐inspection visits (<emph>n</emph> = 4).</p> <p>There is a sizeable difference in the distribution of overall effectiveness grades depending on whether the school employs an Ofsted inspector. Schools that do are around three times more likely to receive an Outstanding rating than those that do not (20% vs 7%). Likewise, at the other extreme, they are also three times less likely to be judged as Requiring Improvement or Inadequate (24% vs 8%). A chi‐squared test confirms that this relationship is statistically significant at the 5% level ( <ephtml> <math altimg="urn:x-wiley:01411926:media:berj4025:berj4025-math-0010" display="inline" overflow="scroll" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msup><mi>χ</mi><mn>2</mn></msup></mrow></semantics></math> </ephtml>  = 29.9; <emph>p</emph> < 0.01). Taken at face value, these results seem to support the hypothesis that schools employing an Ofsted inspector receive more favourable inspection judgements than those that do not.</p> <p>However, under RQ1 above, we noted how some schools (e.g., those with selective intakes and those previously rated as Outstanding) were disproportionately likely to employ an Ofsted inspector, which may confound these results. Consequently, Table 3 reports results from our ordinal logistic regression models. Six specifications are estimated, each including additional controls (see table notes for further details). Estimates are reported in terms of odds ratios, accompanied by their 95% confidence interval.</p> <p>3 TABLE Ordinal logistic regression estimates of the link between a school having a member of staff who conducts inspections on behalf of Ofsted and graded school inspection grade.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">0.28<xref ref-type="fn" rid="tfn4" /></td><td align="left">0.18</td><td align="left">0.46</td></tr><tr><td align="left">M2</td><td align="left">0.34<xref ref-type="fn" rid="tfn4" /></td><td align="left">0.19</td><td align="left">0.56</td></tr><tr><td align="left">M3</td><td align="left">0.35<xref ref-type="fn" rid="tfn4" /></td><td align="left">0.21</td><td align="left">0.57</td></tr><tr><td align="left">M4</td><td align="left">0.37<xref ref-type="fn" rid="tfn4" /></td><td align="left">0.22</td><td align="left">0.61</td></tr><tr><td align="left">M5</td><td align="left">0.35<xref ref-type="fn" rid="tfn4" /></td><td align="left">0.21</td><td align="left">0.58</td></tr><tr><td align="left">M6</td><td align="left">0.37<xref ref-type="fn" rid="tfn4" /></td><td align="left">0.22</td><td align="left">0.61</td></tr></tbody></table> </ephtml> </p> <ulist> <item>3 <emph>Note</emph>: Figures refer to odds ratios. Values below 1 indicate a reduction in the odds of getting a worse overall effectiveness judgement if the school has a member of staff who also works as an OI. M1 captures the bivariate association. M2 controls for school phase, inspection type and number of pupils. M3 adds a control for IDACI quintile. Pupil absences are controlled in M4 and school performance measures in M5. Prior school inspection judgement is controlled in M6. Number of observations = 3147.</item> <item>4 ** Indicates statistical significance at the 5% level. Lower CI/upper CI reports the 95% confidence interval.</item> </ulist> <p>It appears that the controls added to the model can explain only a limited part of the relationship observed in Table 2. In our unconditional model (without any controls), the estimated odds ratio is 0.28. This means that employing an Ofsted inspector reduces the odds of receiving a lower inspection rating (e.g., Requires Improvement/Inadequate rather than Good or Outstanding) by 72%. In our most complete model specification (M6)—which includes a rich set of controls for pupil absence rate, examination performance and prior inspection grade, amongst other factors—the analogous reduction in the odds is 63%. Hence, even after accounting for observable differences in the schools from which the inspection workforce is drawn, we continue to observe a significant advantage amongst schools with an inspector on their payroll.</p> <p>In Table 4, we take this analysis one step further by re‐estimating our model using multinomial logistic regression. This allows us to better differentiate between the effects at the top (i.e., Outstanding vs Good) and bottom (i.e., Good vs Requires Improvement/Inadequate) of the overall effectiveness distribution.</p> <p>4 TABLE Multinomial logistic regression estimates of the link between a school having a member of staff who conducts inspections on behalf of Ofsted and graded school inspection grade.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">(a) Outstanding vs Good</th></tr><tr><th align="left" /><th align="left">Outstanding vs Good</th></tr><tr><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">2.96<xref ref-type="fn" rid="tfn6" /></td><td align="left">1.69</td><td align="left">5.16</td></tr><tr><td align="left">M2</td><td align="left">1.47</td><td align="left">0.79</td><td align="left">2.73</td></tr><tr><td align="left">M3</td><td align="left">1.46</td><td align="left">0.78</td><td align="left">2.72</td></tr><tr><td align="left">M4</td><td align="left">1.43</td><td align="left">0.74</td><td align="left">2.77</td></tr><tr><td align="left">M5</td><td align="left">1.51</td><td align="left">0.78</td><td align="left">2.94</td></tr><tr><td align="left">M6</td><td align="left">1.42</td><td align="left">0.72</td><td align="left">2.77</td></tr></tbody></table> </ephtml> </p> <p></p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">(b) Good vs RI/Inadequate</th></tr><tr><th align="left" /><th align="left">Good vs RI</th></tr><tr><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">0.34<xref ref-type="fn" rid="tfn6" /></td><td align="left">0.16</td><td align="left">0.75</td></tr><tr><td align="left">M2</td><td align="left">0.26<xref ref-type="fn" rid="tfn6" /></td><td align="left">0.11</td><td align="left">0.62</td></tr><tr><td align="left">M3</td><td align="left">0.27<xref ref-type="fn" rid="tfn6" /></td><td align="left">0.11</td><td align="left">0.63</td></tr><tr><td align="left">M4</td><td align="left">0.27<xref ref-type="fn" rid="tfn6" /></td><td align="left">0.11</td><td align="left">0.63</td></tr><tr><td align="left">M5</td><td align="left">0.26<xref ref-type="fn" rid="tfn6" /></td><td align="left">0.11</td><td align="left">0.62</td></tr><tr><td align="left">M6</td><td align="left">0.26<xref ref-type="fn" rid="tfn6" /></td><td align="left">0.11</td><td align="left">0.63</td></tr></tbody></table> </ephtml> </p> <ulist> <item>5 <emph>Note</emph>: Estimates based on multinomial logistic regression models. In panel (a), odds ratios greater than 1 indicate that schools with an OI on their payroll are <emph>more</emph> likely to be rated as Outstanding than Good. In panel (b), values less than 1 indicate that schools with an OI on their payroll are <emph>less</emph> likely to be rated as Requires Improvement or Inadequate rather than Good. M1 captures the bivariate association. M2 controls for school phase, inspection type and number of pupils. M3 adds a control for IDACI quintile. Pupil absences are controlled in M4 and school performance measures in M5. Prior school inspection judgement is controlled in M6. Number of observations = 3147.</item> <item>6 ** Indicates statistical significance at the 5% level. Lower CI/upper CI reports the 95% confidence interval.</item> </ulist> <p>Panel (a) starts by considering the difference between a school being judged as Outstanding rather than Good. Results from the unconditional model confirm that schools employing an inspector are around three times more likely to be awarded the former than the latter (odds ratio around three). Yet this difference is quickly reduced once controls have been added to the model, with the odds ratio falling to around 1.5 in all other model specifications. Our robustness tests in Appendix B—where we also include inspections from the 2021/22 academic year—produce similar results, though with statistical significance fluctuating between the 10% and 5% level. Nevertheless, it seems that the controls added to the model can—to a certain extent—explain why schools employing an Ofsted inspector are more likely to receive an Outstanding grade.</p> <p>Yet the same does not hold true at the other end of the distribution, when we consider the distinction between receipt of a Good rather than a Requires Improvement/Inadequate rating. In the baseline model (M1), the odds of receiving a poor inspection judgement were 66% lower if the school had an inspector on the payroll (odds ratio = 0.34). The inclusion of controls <emph>strengthens</emph> this relationship, with the odds around 75% lower in models M2–M5 (odds ratio ca. 0.25). All these estimates are statistically significant at the 5% level, both in our main analysis and throughout our robustness tests. It thus seems that, in graded inspections, schools employing an Ofsted inspector are much less likely to receive an Inadequate or Requires Improvement rating rather than Good.</p> <p>To conclude our analysis of graded inspections, Table 5 presents results from our ordinal logistic regression models across four sub‐judgements (quality of education, behaviour and attitudes, personal development, leadership and management). These are based on model specification M6, although similar results emerge across other model specifications as well. The intuition behind looking at these sub‐judgements is to establish whether there is any specific area where employing an inspector gives a school a particular advantage.</p> <p>5 TABLE Ordinal logistic regression estimates of the link between a school having a member of staff who conducts inspections on behalf of Ofsted and sub‐judgement outcomes.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">Quality of education</td><td align="left">0.42<xref ref-type="fn" rid="tfn8" /></td><td align="left">0.25</td><td align="left">0.70</td></tr><tr><td align="left">Behaviour & attitudes</td><td align="left">0.29<xref ref-type="fn" rid="tfn8" /></td><td align="left">0.17</td><td align="left">0.48</td></tr><tr><td align="left">Personal development</td><td align="left">0.36<xref ref-type="fn" rid="tfn8" /></td><td align="left">0.22</td><td align="left">0.59</td></tr><tr><td align="left">Leadership & management</td><td align="left">0.39<xref ref-type="fn" rid="tfn8" /></td><td align="left">0.24</td><td align="left">0.64</td></tr></tbody></table> </ephtml> </p> <ulist> <item>7 <emph>Note</emph>: Figures refer to odds ratios. Values below 1 indicate a reduction in the odds of getting a worse overall effectiveness judgement if the school has a member of staff who also works as an OI. Estimates based on model specification M6 which controls for school phase, inspection type, number of pupils, IDACI quintile, pupil absences, school performance measures and prior school inspection judgement. Number of observations = 3147.</item> <item>8 ** Indicates statistical significance at the 5% level. Lower CI/upper CI reports the 95% confidence interval.</item> </ulist> <p>No evidence emerges that this is the case. Schools with an inspector on the payroll tend to receive more favourable judgements across the board, and not just in one or two specific areas. The estimated odds ratios across all four dimensions are statistically significant and reasonably similar in terms of magnitude. This result comes across even more strongly in our robustness tests in Appendix B, with the larger sample size likely aiding the precision and stability of the results. Hence no evidence emerges that schools employing an inspector benefit in just one or two particular areas; judgements tend to be higher across all aspects of their provision.</p> <hd id="AN0180149881-18">Ungraded inspections of previously Good schools</hd> <p>Returning to Table 2, panel (b) illustrates the unconditional distribution of the judgements received by Good schools in ungraded inspections. Here, it seems that schools with inside knowledge seem to benefit more towards the top end of the distribution. In particular, note how schools that employ an inspector are around three times more likely to be judged as potentially improving from Good than schools without an inspector on their payroll (19% vs 6%). The difference at the bottom of the distribution is smaller, with 9% of schools employing an inspector being flagged as potentially declining from Good, compared to 14% of those without an inspector on the books.[<reflink idref="bib6" id="ref48">6</reflink>]</p> <p>Table 6 presents results from our ordinal logistic regression models. Much like the results obtained for graded inspections, the odds ratios move slightly closer to 1 once controls have been added, but not by much. For instance, in the unconditional model (M1), the estimated odds ratio is 0.36; having an inspector working at the school is associated with a 64% decline in the odds of having a worse inspection outcome (e.g., potentially declining from Good relative to remains Good or progress towards Outstanding). Once our school background controls have been added to the model, the analogous reduction in the odds is 53% (odds ratio = 0.47). This remains a sizeable effect, though it only just reaches statistical significance at the 5% level due to the limited sample size. Similar results emerge in Appendix B when data is added from the 2021/22 academic year, though the effect is slightly smaller (a 40% reduction in the odds), which only reaches statistical significance at the 10% threshold.</p> <p>6 TABLE Ordinal logistic regression estimates of the link between a school having a member of staff who conducts inspections on behalf of Ofsted and ungraded school inspection grade.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">0.36<xref ref-type="fn" rid="tfn10" /></td><td align="left">0.17</td><td align="left">0.72</td></tr><tr><td align="left">M2</td><td align="left">0.45<xref ref-type="fn" rid="tfn10" /></td><td align="left">0.22</td><td align="left">0.92</td></tr><tr><td align="left">M3</td><td align="left">0.45<xref ref-type="fn" rid="tfn10" /></td><td align="left">0.22</td><td align="left">0.91</td></tr><tr><td align="left">M4</td><td align="left">0.46<xref ref-type="fn" rid="tfn10" /></td><td align="left">0.23</td><td align="left">0.95</td></tr><tr><td align="left">M5</td><td align="left">0.47<xref ref-type="fn" rid="tfn10" /></td><td align="left">0.23</td><td align="left">0.98</td></tr><tr><td align="left">M6</td><td align="left">0.47<xref ref-type="fn" rid="tfn10" /></td><td align="left">0.23</td><td align="left">0.98</td></tr></tbody></table> </ephtml> </p> <ulist> <item>9 <emph>Note</emph>: Sample based on previously Good schools only. Figures refer to odds ratios. Values below 1 indicate a lower chance of getting a negative inspection outcome (e.g., being graded as Good but concerns—graded inspection next) if the school has a member of staff who also works as an OI. M1 captures the bivariate association. M1 captures the bivariate association. M2 controls for school phase, inspection type and number of pupils. M3 adds a control for IDACI quintile. Pupil absences are controlled in M4 and school performance measures in M5. Prior school inspection judgement is controlled in M6. Number of observations = 2517.</item> <item>10 ** Indicates statistical significance at the 5% level. Lower CI/upper CI reports the 95% confidence interval.</item> </ulist> <p>Finally, to conclude, Table 7 re‐estimates the model using multinomial logistic regression. This again points towards evidence that—for short inspections of previously Good schools—the advantages of having a member of staff who inspects on behalf of Ofsted is mainly observed at the top of the distribution (potential improvement vs no change). Although the addition of background controls slightly attenuates the effect, the odds of a school being judged as potentially improving (rather than no change or remaining Good) are around 2.5 times higher in schools that have an inspector on their payroll. This is observed across model specifications M2 to M6 and is statistically significant at the 5% level. Again, when inspections from the 2021/22 academic year are added in Appendix B, the magnitude of the effect drops slightly (odds ratio ca. 1.9) and only reaches statistical significance at the 10% level. Nevertheless—taken together—the evidence points towards previously Good schools being more likely to be deemed as improving if they employ a school inspector. At the other end of the spectrum, there is less evidence of a difference in terms of the no change versus potential decline judgements (see Table 7, panel b). Qualitatively, results for ungraded inspections of previously Outstanding schools also support this view (see note vi for further details).</p> <p>7 TABLE Multinomial logistic regression estimates of the link between a school having a member of staff who conducts inspections on behalf of Ofsted and ungraded school inspection grade.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">(a) Potential improvement vs no change</th></tr><tr><th align="left" /><th align="left">Improving vs no change</th></tr><tr><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">3.28<xref ref-type="fn" rid="tfn12" /></td><td align="left">1.55</td><td align="left">6.97</td></tr><tr><td align="left">M2</td><td align="left">2.43<xref ref-type="fn" rid="tfn12" /></td><td align="left">1.11</td><td align="left">5.33</td></tr><tr><td align="left">M3</td><td align="left">2.46<xref ref-type="fn" rid="tfn12" /></td><td align="left">1.12</td><td align="left">5.40</td></tr><tr><td align="left">M4</td><td align="left">2.49<xref ref-type="fn" rid="tfn12" /></td><td align="left">1.12</td><td align="left">5.53</td></tr><tr><td align="left">M5</td><td align="left">2.47<xref ref-type="fn" rid="tfn12" /></td><td align="left">1.10</td><td align="left">5.54</td></tr><tr><td align="left">M6</td><td align="left">2.47<xref ref-type="fn" rid="tfn12" /></td><td align="left">1.10</td><td align="left">5.54</td></tr></tbody></table> </ephtml> </p> <p></p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">(b) Potential decline vs no change</th></tr><tr><th align="left" /><th align="left">No change vs decline</th></tr><tr><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">0.69</td><td align="left">0.24</td><td align="left">1.95</td></tr><tr><td align="left">M2</td><td align="left">0.71</td><td align="left">0.25</td><td align="left">2.07</td></tr><tr><td align="left">M3</td><td align="left">0.70</td><td align="left">0.24</td><td align="left">2.02</td></tr><tr><td align="left">M4</td><td align="left">0.69</td><td align="left">0.23</td><td align="left">2.03</td></tr><tr><td align="left">M5</td><td align="left">0.72</td><td align="left">0.24</td><td align="left">2.14</td></tr><tr><td align="left">M6</td><td align="left">0.72</td><td align="left">0.24</td><td align="left">2.14</td></tr></tbody></table> </ephtml> </p> <ulist> <item>11 <emph>Note</emph>: Estimates based on multinomial logistic regression models. In panel (a), odds ratios greater than 1 indicate that schools with an OI on their payroll are <emph>more</emph> likely to be rated as potentially improving rather than no change. In panel (b), values less than 1 indicate that schools with an OI on their payroll are <emph>less</emph> likely to be rated as potentially declining rather than no change. M1 captures the bivariate association. M2 controls for school phase, inspection type and number of pupils. M3 adds a control for IDACI quintile. Pupil absences are controlled in M4 and school performance measures in M5. Prior school inspection judgement is controlled in M6. Number of observations = 2517.</item> <item>12 ** Indicates statistical significance at the 5% level. Lower CI/upper CI reports the 95% confidence interval.</item> </ulist> <hd id="AN0180149881-19">DISCUSSION</hd> <p>Inspections are a central pillar of the school accountability system in England. Given the importance attached to these inspections, it is important that they are sufficiently consistent, reliable, equitable and valid for their intended purpose. An interesting feature of school inspections in England is that many are based on peer review; school leaders from one school make judgements about the provision (according to the criteria set out in the inspection framework) they observe in other schools. Although this system has many benefits, it also has drawbacks as well. One is that it potentially provides a small number of schools with inside knowledge—and hence advantage—in the inspection process. This then raises important questions regarding equity and fairness.</p> <p>We have presented, to our knowledge, the first quantitative evidence on this matter. Using data from nearly 6000 inspections conducted during the 2022/23 academic year, we have illustrated how schools with an Ofsted inspector on their books achieve better inspection outcomes than schools that do not. In particular, they are less likely to receive Requires Improvement or Inadequate judgements from Ofsted's graded inspections, and more likely to be identified as potentially improving during ungraded inspections. These findings survive a series of robustness tests, with the magnitude of the effect remaining similar after a set of key school background characteristics have been controlled for. The evidence hence seems to indicate that there is a potentially sizeable advantage enjoyed by a small number of schools. We also illustrate how, amongst those schools inspected during the 2022/23 academic year, secondary schools, those with selective intakes (grammar schools) and schools previously rated as Outstanding were more likely to have a current Ofsted inspector on their payroll.</p> <p>How do these findings relate to the previous literature? The only prior study we are aware of to investigate how inspector characteristics are linked to inspection outcomes is Bokhove et al. ([<reflink idref="bib4" id="ref49">4</reflink>]). Importantly, they show that contracted OIs (who are the focus of this paper) tend to award more lenient inspection judgements than HMIs. Our work builds on this finding by illustrating how the schools in which these inspectors work also seem to get awarded better inspection outcomes. Hence, not only are OIs more lenient judges, but they (or, rather, their schools) may also get more leniently judged themselves.</p> <p>However, before jumping to this conclusion, it is important to return to the mechanisms potentially driving our findings as set out in the Introduction. The possibility that schools with a serving Ofsted inspector get judged more leniently during inspections (e.g., due to professional network effects) is just one potential explanation for our results. Without further data, we are unable to establish whether our results could reflect the 'human capital' effect of being trained and employed as an Ofsted inspector (i.e., that this helps to develop the leader's skills, which helps them to improve provision within their own school). Indeed, it seems that the incoming HMCI may be of this view: 'I often hear about how good the inspector training is and it seems to me to be entirely sensible that this professional development of serving leaders should not only support inspections but also be used to raise standards in those leaders' own institutions' (UK Parliament, [<reflink idref="bib32" id="ref50">32</reflink>]). Yet our findings could also potentially be the result of these individuals becoming better at managing the inspection process, knowing what and how to prepare, how to act during the inspection and what to say.</p> <p>Ultimately, to probe this important issue further, we require more data and insights in the overall inspection process. This will, in turn, require a greater willingness from school inspectorates to share such information for research purposes. The fact that the data used in this paper was obtained by journalists using freedom of information legislation—and even then, only after the Information Commissioner's Office stepped in to force its release—illustrates the challenges researchers currently face. We thus repeat calls we have made previously for an inspection–inspector linked database to be made available in the Office for National Statistics Integrated Data Service to facilitate further research into school inspections in England (Bokhove et al., [<reflink idref="bib5" id="ref51">5</reflink>]).</p> <p>Of course, there are limitations to our work, many of which stem from this lack of data availability. First, as noted above, we are unable to probe in any great detail the potential mechanisms driving our results. Second, while the addition of most school‐level controls did not substantially alter our key findings, we cannot rule out the possibility that unobserved confounders may to some extent attenuate our estimates. Third, the sample size available remains relatively limited; just 150 inspections conducted in the 2022/23 academic year were of a school where a serving Ofsted inspector works. Although our findings are largely unchanged when inspections from the previous (2021/22) academic year are also included, information from further timepoints would enhance the precision of our estimates. Finally, the inspections conducted during this time were—for most schools—the first time they had been inspected under the latest Ofsted framework (introduced in September 2019). It is not clear whether, once schools have more experience of this framework (e.g., have been inspected under it more than once), the value of inside information may diminish. With further data, this is another issue that could be investigated in future work.</p> <p>Despite these limitations, our findings have at least three important implications for inspection policy. Sector leaders in England have been arguing for some time that the material used to train inspectors should be released into the public domain. On balance, we believe that our findings support these calls, regardless of which mechanisms are driving our results. For instance, if the training Ofsted provides really does boost inspectors' 'human capital'—and lead to school improvement—then such 'best practise' should be shared as far and widely as possible. If, on the other hand, these materials give OIs an advantage in terms of knowing what to say, do or prepare for an inspection, then it does seem unfair that others are not privy to such information. While we recognise that providing these materials may have some resource implications—to ensure they are properly understood and contextualised—we can also see important benefits in creating high‐quality digital resources that can complement the handbooks, webinars and seminars that Ofsted already provides.</p> <p>Second, depending on the specific mechanism that is driving our findings, the results may have broader implications regarding the professional development of school leaders. For instance, it is possible that the difference in outcomes we observe is partly due to headteachers improving their own practice from regularly having the opportunity to observe what is happening in other local schools. If this is indeed the case, then it suggests that peer observation should be a key part of leaders' professional development in all schools—either by working as an inspector or an alternative collaborative approach. Alternatively, it may be possible that the training provided to inspectors by Ofsted genuinely improves inspectors' school leadership skills. If this is true, it suggests that Ofsted should consider making its training available to all headteachers. This again points towards the importance of future research disentangling the mechanisms that are driving the associations we observe.</p> <p>Third, while we don't know the extent to which our results are driven by professional network effects, it is vital that the risks of these are minimised to maintain the face validity of inspections. We are unsure of Ofsted's existing policy in this area but, from scanning a selection of inspection reports, it appears that schools employing an Ofsted inspector continue to be inspected by teams from within the same region (though usually with an HMI as the lead). This may be something that Ofsted wishes to clarify. Although there may be logistical challenges, our suggestion is that—in the future—schools that employ an OI are inspected by teams from other parts of the country. For instance, if a school in the South East has an OI on their books, then they should be inspected by a team of inspectors from (for instance) the North West. This should be possible, given the small number of inspections that this issue affects. While not a foolproof solution, it would nevertheless help to limit the amount of previous contact these schools would have had with their inspectors.</p> <hd id="AN0180149881-20">ACKNOWLEDGEMENTS</hd> <p>The Nuffield Foundation is an independent charitable trust with a mission to advance social wellbeing. It funds research that informs social policy, primarily in Education, Welfare and Justice. It also funds student programmes that provide opportunities for young people to develop skills in quantitative and scientific methods. The Nuffield Foundation is the founder and co‐funder of the Nuffield Council on Bioethics and the Ada Lovelace Institute. The Foundation has funded this project, but the views expressed are those of the authors and not necessarily the Foundation. Visit <ulink href="http://www.nuffieldfoundation.org">www.nuffieldfoundation.org</ulink>.</p> <hd id="AN0180149881-21">FUNDING INFORMATION</hd> <p>This paper was funded by the Nuffield Foundation. The Nuffield Foundation is an independent charitable trust with a mission to advance social wellbeing. It funds research that informs social policy, primarily in Education, Welfare and Justice. It also funds student programmes that provide opportunities for young people to develop skills in quantitative and scientific methods. The Nuffield Foundation is the founder and co‐funder of the Nuffield Council on Bioethics and the Ada Lovelace Institute. The Foundation has funded this project, but the views expressed are those of the authors and not necessarily the Foundation. Visit <ulink href="http://www.nuffieldfoundation.org">www.nuffieldfoundation.org</ulink>.</p> <hd id="AN0180149881-22">CONFLICT OF INTEREST STATEMENT</hd> <p>The author declares that there is no conflict of interest.</p> <hd id="AN0180149881-23">DATA AVAILABILITY STATEMENT</hd> <p>The data used in this paper was obtained from journalists at <emph>Schools Week</emph> under a freedom of information request.</p> <hd id="AN0180149881-24">ETHICS STATEMENT</hd> <p>The BERA code of ethics has been followed in producing this paper.</p> <hd id="AN0180149881-25">A APPENDIX Data quality checks</hd> <p>To check the quality of the data, we have randomly sampled 100 of the schools contained within the original list provided by Ofsted to <emph>School Weeks</emph> in response to their freedom of information request. For these 100 schools, we then conducted an exercise similar to what the journalists did for all 762 schools. Namely, we used the Department of Education's Get Information About Schools service (<ulink href="http://www.get-information-schools.service.gov.uk">http://www.get-information-schools.service.gov.uk</ulink>) to establish the URN of the school (the key identifier that we use to merge further information from external sources). This was done blind to the URN obtained by <emph>Schools Week</emph>. It thus serves as a measure of inter‐rater reliability of our key variable—schools where at least one staff member is an Ofsted inspector.</p> <p>Out of the 100 schools considered, the URN that we assigned matched that assigned by the journalists from <emph>Schools Week</emph> on 96 occasions. Of the remaining four schools, we did not assign a URN to three of them, due to potential ambiguity surrounding the school name (e.g., there was more than one school that we deemed to be the most likely match). Hence there was just one school out of the 100 where we assigned a different URN to the school than journalists from <emph>Schools Week</emph>. Out of the 100 randomly selected schools, we did not find a successful URN match on 18 occasions. However, around half of these were due to the OI not working at a school, but a different type of establishment (e.g., University of Warwick, Lincolnshire County Council, The Lighthouse Learning Hub Community Interest Company).</p> <hd id="AN0180149881-26">B APPENDIX Alternative estimates based upon inspections conducted in the 2021/22 and 2022/23...</hd> <p>B1 TABLE Ordinal logistic regression estimates of the link between a school having a member of staff who conducts inspections on behalf of Ofsted and graded school inspection grade. Results including data from the 2021/22 academic year.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">0.24<xref ref-type="fn" rid="tfn14" /></td><td align="left">0.16</td><td align="left">0.35</td></tr><tr><td align="left">M2</td><td align="left">0.29<xref ref-type="fn" rid="tfn14" /></td><td align="left">0.19</td><td align="left">0.44</td></tr><tr><td align="left">M3</td><td align="left">0.29<xref ref-type="fn" rid="tfn14" /></td><td align="left">0.19</td><td align="left">0.45</td></tr><tr><td align="left">M4</td><td align="left">0.33<xref ref-type="fn" rid="tfn14" /></td><td align="left">0.22</td><td align="left">0.50</td></tr><tr><td align="left">M5</td><td align="left">0.31<xref ref-type="fn" rid="tfn14" /></td><td align="left">0.20</td><td align="left">0.48</td></tr><tr><td align="left">M6</td><td align="left">0.33<xref ref-type="fn" rid="tfn14" /></td><td align="left">0.21</td><td align="left">0.50</td></tr></tbody></table> </ephtml> </p> <ulist> <item>13 <emph>Note</emph>: Figures refer to odds ratios. Values below 1 indicate a reduction in the odds of getting a worse overall effectiveness judgement if the school has a member of staff who also works as an OI. M1 captures the bivariate association. M2 controls for school phase, inspection type and number of pupils. M3 adds a control for IDACI quintile. Pupil absences are controlled in M4 and school performance measures in M5. Prior school inspection judgement is controlled in M6. Number of observations = 4990.</item> <item>14 Indicates statistical significance at the 5% level. Lower CI/upper CI reports the 95% confidence interval.</item> </ulist> <p>B2 TABLE Multinomial logistic regression estimates of the link between a school having a member of staff who conducts inspections on behalf of Ofsted and graded school inspection grade. Results including data from the 2021/22 academic year.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">(a) Outstanding vs Good</th></tr><tr><th align="left" /><th align="left">Outstanding vs Good</th></tr><tr><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">3.67**</td><td align="left">2.32</td><td align="left">5.80</td></tr><tr><td align="left">M2</td><td align="left">1.89**</td><td align="left">1.14</td><td align="left">3.14</td></tr><tr><td align="left">M3</td><td align="left">1.88**</td><td align="left">1.13</td><td align="left">3.13</td></tr><tr><td align="left">M4</td><td align="left">1.63*</td><td align="left">0.95</td><td align="left">2.81</td></tr><tr><td align="left">M5</td><td align="left">1.82**</td><td align="left">1.05</td><td align="left">3.16</td></tr><tr><td align="left">M6</td><td align="left">1.70*</td><td align="left">0.97</td><td align="left">2.96</td></tr></tbody></table> </ephtml> </p> <p></p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">(b) Good vs RI/Inadequate</th></tr><tr><th align="left" /><th align="left">Good vs RI</th></tr><tr><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">0.34**</td><td align="left">0.18</td><td align="left">0.63</td></tr><tr><td align="left">M2</td><td align="left">0.29**</td><td align="left">0.15</td><td align="left">0.57</td></tr><tr><td align="left">M3</td><td align="left">0.30**</td><td align="left">0.15</td><td align="left">0.58</td></tr><tr><td align="left">M4</td><td align="left">0.31**</td><td align="left">0.16</td><td align="left">0.61</td></tr><tr><td align="left">M5</td><td align="left">0.31**</td><td align="left">0.16</td><td align="left">0.60</td></tr><tr><td align="left">M6</td><td align="left">0.31**</td><td align="left">0.16</td><td align="left">0.61</td></tr></tbody></table> </ephtml> </p> <p>15 <emph>Note</emph>: Estimates based on multinomial logistic regression models. In panel (a), odds ratios greater than 1 indicate that schools with an OI on their payroll are <emph>more</emph> likely to be rated as Outstanding than Good. In panel (b), values less than 1 indicate that schools with an OI on their payroll are <emph>less</emph> likely to be rated as Requires Improvement or Inadequate rather than Good. M1 captures the bivariate association. M2 controls for school phase, inspection type and number of pupils. M3 adds a control for IDACI quintile. Pupil absences are controlled in M4 and school performance measures in M5. Prior school inspection judgement is controlled in M6. Number of observations = 4990. * and ** indicate statistical significance at the 10% and 5% level, respectively. Lower CI/upper CI reports the 95% confidence interval.</p> <p>B3 TABLE Ordinal logistic regression estimates of the link between a school having a member of staff who conducts inspections on behalf of Ofsted and sub‐judgement outcomes. Results including data from the 2021/22 academic year.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">Quality of education</td><td align="left">0.36<xref ref-type="fn" rid="tfn17" /></td><td align="left">0.23</td><td align="left">0.55</td></tr><tr><td align="left">Behaviour & attitudes</td><td align="left">0.34<xref ref-type="fn" rid="tfn17" /></td><td align="left">0.22</td><td align="left">0.51</td></tr><tr><td align="left">Personal development</td><td align="left">0.35<xref ref-type="fn" rid="tfn17" /></td><td align="left">0.23</td><td align="left">0.52</td></tr><tr><td align="left">Leadership & management</td><td align="left">0.37<xref ref-type="fn" rid="tfn17" /></td><td align="left">0.24</td><td align="left">0.55</td></tr></tbody></table> </ephtml> </p> <ulist> <item>16 <emph>Note</emph>: Figures refer to odds ratios. Values below 1 indicate a reduction in the odds of getting a worse overall effectiveness judgement if the school has a member of staff who also works as an OI. Estimates based on model specification M6 which controls for school phase, inspection type, number of pupils, IDACI quintile, pupil absences, school performance measures and prior school inspection judgement. Number of observations = 4990.</item> <item>17 Indicates statistical significance at the 5% level. Lower CI/upper CI reports the 95% confidence interval.</item> </ulist> <p>B4 TABLE Ordinal logistic regression estimates of the link between a school having a member of staff that conducts inspections on behalf of Ofsted and ungraded school inspection grade. Results including data from the 2021/22 academic year.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">0.43**</td><td align="left">0.24</td><td align="left">0.76</td></tr><tr><td align="left">M2</td><td align="left">0.57*</td><td align="left">0.32</td><td align="left">1.02</td></tr><tr><td align="left">M3</td><td align="left">0.57*</td><td align="left">0.32</td><td align="left">1.02</td></tr><tr><td align="left">M4</td><td align="left">0.59*</td><td align="left">0.33</td><td align="left">1.06</td></tr><tr><td align="left">M5</td><td align="left">0.60*</td><td align="left">0.33</td><td align="left">1.07</td></tr><tr><td align="left">M6</td><td align="left">0.60*</td><td align="left">0.33</td><td align="left">1.07</td></tr></tbody></table> </ephtml> </p> <ulist> <item>18 <emph>Note</emph>: Sample based on previously Good schools only. Figures refer to odds ratios. Values below 1 indicate a lower chance of getting a negative inspection outcome (e.g., being graded as Good but concerns—graded inspection next) if the school has a member of staff who also works as an OI. M1 captures the bivariate association. M2 controls for school phase, inspection type and number of pupils. M3 adds a control for IDACI quintile. Pupil absences are controlled in M4 and school performance measures in M5. Prior school inspection judgement is controlled in M6. Number of observations = 4089.</item> <item>19 * and ** indicate statistical significance at the 10% and 5% level, respectively. Lower CI/upper CI reports the 95% confidence interval.</item> </ulist> <p>B5 TABLE Multinomial logistic regression estimates of the link between a school having a member of staff who conducts inspections on behalf of Ofsted and ungraded school inspection grade. Results including data from the 2021/22 academic year.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">(a) Potential improvement vs no change</th></tr><tr><th align="left" /><th align="left">Improving vs no change</th></tr><tr><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">2.59**</td><td align="left">1.34</td><td align="left">5.00</td></tr><tr><td align="left">M2</td><td align="left">1.80*</td><td align="left">0.90</td><td align="left">3.60</td></tr><tr><td align="left">M3</td><td align="left">1.80*</td><td align="left">0.90</td><td align="left">3.60</td></tr><tr><td align="left">M4</td><td align="left">1.88*</td><td align="left">0.94</td><td align="left">3.78</td></tr><tr><td align="left">M5</td><td align="left">1.88*</td><td align="left">0.93</td><td align="left">3.81</td></tr><tr><td align="left">M6</td><td align="left">1.88*</td><td align="left">0.93</td><td align="left">3.81</td></tr></tbody></table> </ephtml> </p> <p></p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">(b) Potential decline vs no change</th></tr><tr><th align="left" /><th align="left">No change vs decline</th></tr><tr><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">0.63</td><td align="left">0.28</td><td align="left">1.38</td></tr><tr><td align="left">M2</td><td align="left">0.74</td><td align="left">0.33</td><td align="left">1.66</td></tr><tr><td align="left">M3</td><td align="left">0.74</td><td align="left">0.33</td><td align="left">1.66</td></tr><tr><td align="left">M4</td><td align="left">0.76</td><td align="left">0.34</td><td align="left">1.71</td></tr><tr><td align="left">M5</td><td align="left">0.77</td><td align="left">0.34</td><td align="left">1.74</td></tr><tr><td align="left">M6</td><td align="left">0.77</td><td align="left">0.34</td><td align="left">1.74</td></tr></tbody></table> </ephtml> </p> <p>20 <emph>Note</emph>: Estimates based on multinomial logistic regression models. In panel (a), odds ratios greater than 1 indicate that schools with an OI on their payroll are <emph>more</emph> likely to be rated as potentially improving rather than no change. In panel (b), values less than 1 indicate that schools with an OI on their payroll are <emph>less</emph> likely to be rated as potentially declining rather than no change. M1 captures the bivariate association. M2 controls for school phase, inspection type and number of pupils. M3 adds a control for IDACI quintile. Pupil absences are controlled in M4 and school performance measures in M5. Prior school inspection judgement is controlled in M6. Number of observations = 4089. * and ** indicate statistical significance at the 10% and 5% level, respectively. Lower CI/upper CI reports the 95% confidence interval.</p> <hd id="AN0180149881-27">C APPENDIX Alternative estimates combining information across graded and ungraded inspections</hd> <p>C1 TABLE Ordinal logistic regression estimates of the link between a school having a member of staff who conducts inspections on behalf of Ofsted. Results combining information from graded and ungraded inspections.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">0.31<xref ref-type="fn" rid="tfn22" /></td><td align="left">0.21</td><td align="left">0.46</td></tr><tr><td align="left">M2</td><td align="left">0.37<xref ref-type="fn" rid="tfn22" /></td><td align="left">0.25</td><td align="left">0.57</td></tr><tr><td align="left">M3</td><td align="left">0.38<xref ref-type="fn" rid="tfn22" /></td><td align="left">0.25</td><td align="left">0.57</td></tr><tr><td align="left">M4</td><td align="left">0.40<xref ref-type="fn" rid="tfn22" /></td><td align="left">0.26</td><td align="left">0.60</td></tr><tr><td align="left">M5</td><td align="left">0.39<xref ref-type="fn" rid="tfn22" /></td><td align="left">0.26</td><td align="left">0.59</td></tr><tr><td align="left">M6</td><td align="left">0.41<xref ref-type="fn" rid="tfn22" /></td><td align="left">0.27</td><td align="left">0.62</td></tr></tbody></table> </ephtml> </p> <ulist> <item>21 <emph>Note</emph>: Figures refer to odds ratios. Outcome variable is coded 1 if the school received an Outstanding judgement from a graded inspection or an 'improving' outcome from an ungraded inspection. It is coded 2 if the school received a Good judgement from a graded inspection or the school remained Good (no change) from an ungraded inspection. Finally, it is coded 3 for an Inadequate or Requires Improvement rating from a graded inspection, or concerns raised from an ungraded inspection. Values below 1 indicate a reduction in the odds of getting a worse inspection judgement if the school has a member of staff who also works as an OI. M1 captures the bivariate association. M2 controls for school phase, inspection type and number of pupils. M3 adds a control for IDACI quintile. Pupil absences are controlled in M4 and school performance measures in M5. Prior school inspection judgement is controlled in M6. Number of observations = 5664.</item> <item>22 Indicates statistical significance at the 5% level. Lower CI/upper CI reports the 95% confidence interval.</item> </ulist> <p>C2 TABLE Multinomial logistic regression estimates of the link between a school having a member of staff who conducts inspections on behalf of Ofsted and school inspection outcomes. Results combining information from graded and ungraded inspections.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">(a) Positive outcome vs neutral outcome</th></tr><tr><th align="left" /><th align="left">Positive vs neutral</th></tr><tr><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">3.13**</td><td align="left">2.00</td><td align="left">4.90</td></tr><tr><td align="left">M2</td><td align="left">1.75**</td><td align="left">1.08</td><td align="left">2.86</td></tr><tr><td align="left">M3</td><td align="left">1.75**</td><td align="left">1.08</td><td align="left">2.86</td></tr><tr><td align="left">M4</td><td align="left">1.72**</td><td align="left">1.04</td><td align="left">2.85</td></tr><tr><td align="left">M5</td><td align="left">1.76**</td><td align="left">1.06</td><td align="left">2.94</td></tr><tr><td align="left">M6</td><td align="left">1.67*</td><td align="left">1.00</td><td align="left">2.80</td></tr></tbody></table> </ephtml> </p> <p></p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">(b) Neutral outcome vs disappointing outcome</th></tr><tr><th align="left" /><th align="left">Neutral vs disappointing</th></tr><tr><th align="left">Odds ratio</th><th align="left">Lower CI</th><th align="left">Upper CI</th></tr></thead><tbody valign="top"><tr><td align="left">M1</td><td align="left">0.45**</td><td align="left">0.24</td><td align="left">0.84</td></tr><tr><td align="left">M2</td><td align="left">0.38**</td><td align="left">0.20</td><td align="left">0.75</td></tr><tr><td align="left">M3</td><td align="left">0.38**</td><td align="left">0.20</td><td align="left">0.75</td></tr><tr><td align="left">M4</td><td align="left">0.38**</td><td align="left">0.20</td><td align="left">0.75</td></tr><tr><td align="left">M5</td><td align="left">0.38**</td><td align="left">0.20</td><td align="left">0.75</td></tr><tr><td align="left">M6</td><td align="left">0.39**</td><td align="left">0.20</td><td align="left">0.76</td></tr></tbody></table> </ephtml> </p> <p>23 <emph>Note</emph>: Estimates based on multinomial logistic regression models. Outcome variable is coded 1 if the school received an Outstanding judgement from a graded inspection or an 'improving' outcome from an ungraded inspection. It is coded 2 if the school received a Good judgement from a graded inspection or the school remained Good (no change) from an ungraded inspection. Finally, it is coded 3 for an Inadequate or Requires Improvement rating from a graded inspection, or concerns raised from an ungraded inspection. In panel (a), odds ratios greater than 1 indicate that schools with an OI on their payroll are <emph>more</emph> likely to have a positive outcome from the inspection (compared to a neutral outcome). In panel (b), values less than 1 indicate that schools with an OI on their payroll are <emph>less</emph> likely to have a disappointing outcome from the school inspection (as compared to a neutral outcome). M1 captures the bivariate association. M2 controls for school phase, inspection type and number of pupils. M3 adds a control for IDACI quintile. Pupil absences are controlled in M4 and school performance measures in M5. Prior school inspection judgement is controlled in M6. Number of observations = 5664. * and ** indicate statistical significance at the 10% and 5% level, respectively. Lower CI/upper CI reports the 95% confidence interval.</p> <ref id="AN0180149881-28"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref23" type="bt">1</bibl> <bibtext> Where there was some ambiguity regarding the exact school (due, for instance, to some schools having very similar names), what was deemed the most likely option was selected.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref1" type="bt">2</bibl> <bibtext> At the time of writing, no more recent school‐level information was available due to school performance data not being published following the COVID‐19 pandemic.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref17" type="bt">3</bibl> <bibtext> There were just 16 inspections of previously Outstanding schools in the 2022/23 academic year that employed an Ofsted inspector.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref9" type="bt">4</bibl> <bibtext> The resulting variable is coded 1 for Outstanding (graded) and improving (ungraded) schools, 2 for Good (graded) and unchanged (ungraded) schools and 3 for Requires Improvement/Inadequate (graded) and schools where there are concerns (ungraded).</bibtext> </blist> <blist> <bibl id="bib5" idref="ref38" type="bt">5</bibl> <bibtext> When including inspections from the 2021/22 academic year as well, the number of selective secondary schools increases to 91, with 11% of these identified as employing an Ofsted inspector.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref42" type="bt">6</bibl> <bibtext> Of the 16 previously Outstanding schools that employed an Ofsted inspector that were inspected in the 2022/23 academic year, 9 (56%) were flagged as potentially declining. This compares to 41% of previously Outstanding schools inspected that did not employ an inspector. Although the difference is reasonably sizeable—and in the opposite direction to the results for schools previously rated as Good—the small sample means it does not reach statistical significance ( <ephtml> <math altimg="urn:x-wiley:01411926:media:berj4025:berj4025-math-0011" display="inline" overflow="scroll" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msup><mi>χ</mi><mn>2</mn></msup></mrow></semantics></math> </ephtml> = 1.46; <emph>p</emph> = 0.23). The sparse cell sizes mean we are unable to implement our regression modelling approach to probe this difference further.</bibtext> </blist> </ref> <ref id="AN0180149881-29"> <title> REFERENCES </title> <blist> <bibtext> Association of School and College Leaders. (2023). The future of inspection. An ASCL Discussion Paper. https://<ulink href="http://www.ascl.org.uk/ASCL/media/ASCL/Our%20view/Campaigns/The‐future‐of‐inspection‐an‐ASCL‐discussion‐paper.pdf">www.ascl.org.uk/ASCL/media/ASCL/Our%20view/Campaigns/The‐future‐of‐inspection‐an‐ASCL‐discussion‐paper.pdf</ulink></bibtext> </blist> <blist> <bibtext> Barbana, S., Dumay, X., & Dupriez, V. (2020). Accountability policy forms in European education systems: An introduction. European Educational Research Journal, 19 (2), 87 – 93. https://doi.org/10.1177/1474904120907252</bibtext> </blist> <blist> <bibtext> Becker, G. (1962). Investment in human capital: A theoretical analysis. The Journal of Political Economy, 70 (5), 9 – 49.</bibtext> </blist> <blist> <bibtext> Bokhove, C., Jerrim, J., & Sims, S. (2023a). How useful are Ofsted inspection judgements for informing secondary school choice? Journal of School Choice, 17 (1), 35 – 61. https://doi.org/10.1080/15582159.2023.2169813</bibtext> </blist> <blist> <bibtext> Bokhove, C., Jerrim, J., & Sims, S. (2023b). Are some school inspectors more lenient than others? School Effectiveness and School Improvement, 34, 419 – 441. https://doi.org/10.1080/09243453.2023.2240318</bibtext> </blist> <blist> <bibtext> Cinelli, C., Forney, A., & Pearl, J. (2022). A crash course in good and bad controls. Sociological Methods & Research. https://doi.org/10.1177/00491241221099552</bibtext> </blist> <blist> <bibl id="bib7" idref="ref31" type="bt">7</bibl> <bibtext> Colman, A. (2022). School leadership, inspection and visibility: Panopticism and post‐panopticism in an English coastal area of deprivation. British Journal of Educational Studies, 70 (1), 3 – 19.</bibtext> </blist> <blist> <bibl id="bib8" idref="ref29" type="bt">8</bibl> <bibtext> Courtney, S. J. (2013). Head teachers' experiences of school inspection under Ofsted's January 2012 framework. Management in Education, 27 (4), 164 – 169. https://doi.org/10.1177/0892020613498408</bibtext> </blist> <blist> <bibl id="bib9" idref="ref32" type="bt">9</bibl> <bibtext> Cushing, I., & Snell, J. (2023). The (white) ears of Ofsted: A raciolinguistic perspective on the listening practices of the schools inspectorate. Language in Society, 52 (3), 363 – 386. https://doi.org/10.1017/S0047404522000094</bibtext> </blist> <blist> <bibtext> de Wolf, I. F., & Janssens, F. J. G. (2007). Effects and side effects of inspections and accountability in education: An overview of empirical studies. Oxford Review of Education, 33 (3), 379 – 396. <ulink href="http://www.jstor.org/stable/20462342">http://www.jstor.org/stable/20462342</ulink></bibtext> </blist> <blist> <bibtext> Ehren, M. C. M., Gustafsson, J. E., Altrichter, H., Skedsmo, G., Kemethofer, D., & Huber, S. G. (2015). Comparing effects and side effects of different school inspection systems across Europe. Comparative Education, 51 (3), 375 – 400. https://doi.org/10.1080/03050068.2015.1045769</bibtext> </blist> <blist> <bibtext> Ehren, M., Jones, K., & Perryman, J. (2016). Side effects of school inspection; motivations and contexts for strategic responses. In M. Ehren (Ed.), Methods and modalities of effective school inspections (pp. 87 – 109). Springer. https://doi.org/10.1007/978‐3‐319‐31003‐9_5</bibtext> </blist> <blist> <bibtext> Eyles, A., & Machin, S. (2019). The introduction of academy schools to England's education. Journal of the European Economic Association, 17 (4), 1107 – 1146. https://doi.org/10.1093/jeea/jvy021</bibtext> </blist> <blist> <bibtext> Jones, K., & Tymms, P. (2014). Ofsted's role in promoting school improvement: The mechanisms of the school inspection system in England. Oxford Review of Education, 40 (3), 315 – 330. https://doi.org/10.1080/03054985.2014.911726</bibtext> </blist> <blist> <bibtext> Matthews, P., Holmes, J. R., Vickers, P., & Corporaal, B. (1998). Aspects of the reliability and validity of school inspection judgements of teaching quality. Educational Research and Evaluation, 4 (2), 167 – 188. https://doi.org/10.1076/edre.4.2.167.6959</bibtext> </blist> <blist> <bibtext> Moreton, H. J., Boylan, M., & Simkins, T. (2017). Headteachers who also inspect: Practitioner inspectors in England. In Baxter, J. (Ed.), School inspectors: Accountability and educational improvement (pp. 137–158). Springer. https://doi.org/10.1007/978‐3‐319‐52536‐5_7</bibtext> </blist> <blist> <bibtext> OECD. (2019). Education GPS: School evaluation. https://gpseducation.oecd.org/revieweducationpolicies/#!node=41743&filter=all</bibtext> </blist> <blist> <bibtext> Office for Standards in Education. (2017). Do two inspectors inspecting the same school make consistent decisions? A study of the reliability of Ofsted's new short inspections. Ofsted Research Report 170004. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/596708/Reliability_study_‐_final.pdf</bibtext> </blist> <blist> <bibtext> Office for Standards in Education. (2019a). How valid and reliable is the use of lesson observation in supporting judgements on the quality of education? Ofsted Research Report 190029. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/936246/Inspecting_education_quality_Lesson_observation_report.pdf</bibtext> </blist> <blist> <bibtext> Office for Standards in Education. (2019b). Workbook scrutiny: Ensuring validity and reliability in inspections. Ofsted Research Report 190028. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/936240/Inspecting_education_quality_workbook_scrutiny_report.pdf</bibtext> </blist> <blist> <bibtext> Office for Standards in Education. (2022). Contracted Ofsted inspectors for schools and further education and skills. https://<ulink href="http://www.gov.uk/guidance/contracted‐ofsted‐inspectors‐for‐schools‐and‐further‐education‐and‐skills">www.gov.uk/guidance/contracted‐ofsted‐inspectors‐for‐schools‐and‐further‐education‐and‐skills</ulink></bibtext> </blist> <blist> <bibtext> Office for Standards in Education. (2023a). School inspection handbook. https://<ulink href="http://www.gov.uk/government/publications/school‐inspection‐handbook‐eif">www.gov.uk/government/publications/school‐inspection‐handbook‐eif</ulink></bibtext> </blist> <blist> <bibtext> Office for Standards in Education. (2023b). Contracted Ofsted inspectors for schools and further education and skills. https://<ulink href="http://www.gov.uk/guidance/contracted‐ofsted‐inspectors‐for‐schools‐and‐further‐education‐and‐skills">www.gov.uk/guidance/contracted‐ofsted‐inspectors‐for‐schools‐and‐further‐education‐and‐skills</ulink></bibtext> </blist> <blist> <bibtext> Office for Standards in Education. (2023c). Conflicts of interest: Policy and procedure for contracted Ofsted inspectors. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/823749/Conflicts_of_interest_policy_and_procedure_for_Ofsted_Inspectors.doc</bibtext> </blist> <blist> <bibtext> Page, D. (2017). Conceptualising the surveillance of teachers. British Journal of Sociology of Education, 38 (7), 991 – 1006. https://doi.org/10.1080/01425692.2016.1218752</bibtext> </blist> <blist> <bibtext> Perryman, J. (2007). Inspection and emotion. Cambridge Journal of Education, 37 (2), 173 – 190. https://doi.org/10.1080/03057640701372418</bibtext> </blist> <blist> <bibtext> Perryman, J., Maguire, M., Braun, A., & Ball, S. (2017). Surveillance, governmentality and moving the goalposts: The influence of Ofsted on the work of schools in a post‐panoptic era. British Journal of Educational Studies, 66 (2), 145 – 163. https://doi.org/10.1080/00071005.2017.1372560</bibtext> </blist> <blist> <bibtext> Ponzo, M., & Scoppa, V. (2011). A simple model of favouritism in recruitment. Research in Economics, 65 (2), 78 – 88. https://doi.org/10.1016/j.rie.2010.09.003</bibtext> </blist> <blist> <bibtext> Stiglitz, J. E. (1975). The theory of "screening," education, and the distribution of income. The American Economic Review, 65 (3), 283 – 300.</bibtext> </blist> <blist> <bibtext> Tian, M. (2023). A critical friend or the sword of Damocles: Headteachers' use of micropolitical strategies in inspection. Educational Management Administration & Leadership, 1 – 18. https://doi.org/10.1177/17411432231222719</bibtext> </blist> <blist> <bibtext> UK Parliament. (2023). Ofsted's work with schools. Written evidence by the Association of School and College Leaders (ASCL). https://committees.parliament.uk/writtenevidence/122799/pdf/</bibtext> </blist> <blist> <bibtext> UK Parliament. (2023b). Appointment of His Majesty's Chief Inspector of Education, Children's Services and Skills. https://publications.parliament.uk/pa/cm5803/cmselect/cmeduc/1800/report.html#heading‐8</bibtext> </blist> <blist> <bibtext> Walker, A. (2022). Ofsted snubs calls to publish inspector training guides. https://schoolsweek.co.uk/ofsted‐snubs‐calls‐to‐publish‐inspector‐training‐guides/</bibtext> </blist> <blist> <bibtext> Walker, A. (2023). Trust leaders more likely to work part‐time for Ofsted. https://schoolsweek.co.uk/trust‐leaders‐more‐likely‐to‐work‐part‐time‐for‐ofsted/</bibtext> </blist> </ref> <aug> <p>By Christian Bokhove; John Jerrim and Sam Sims</p> <p>Reported by Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib17" firstref="ref2"></nolink> <nolink nlid="nl2" bibid="bib14" firstref="ref3"></nolink> <nolink nlid="nl3" bibid="bib10" firstref="ref4"></nolink> <nolink nlid="nl4" bibid="bib11" firstref="ref5"></nolink> <nolink nlid="nl5" bibid="bib26" firstref="ref6"></nolink> <nolink nlid="nl6" bibid="bib27" firstref="ref7"></nolink> <nolink nlid="nl7" bibid="bib12" firstref="ref8"></nolink> <nolink nlid="nl8" bibid="bib13" firstref="ref10"></nolink> <nolink nlid="nl9" bibid="bib16" firstref="ref11"></nolink> <nolink nlid="nl10" bibid="bib22" firstref="ref12"></nolink> <nolink nlid="nl11" bibid="bib23" firstref="ref15"></nolink> <nolink nlid="nl12" bibid="bib29" firstref="ref18"></nolink> <nolink nlid="nl13" bibid="bib34" firstref="ref19"></nolink> <nolink nlid="nl14" bibid="bib24" firstref="ref20"></nolink> <nolink nlid="nl15" bibid="bib28" firstref="ref21"></nolink> <nolink nlid="nl16" bibid="bib33" firstref="ref22"></nolink> <nolink nlid="nl17" bibid="bib31" firstref="ref24"></nolink> <nolink nlid="nl18" bibid="bib32" firstref="ref25"></nolink> <nolink nlid="nl19" bibid="bib30" firstref="ref26"></nolink> <nolink nlid="nl20" bibid="bib25" firstref="ref33"></nolink> <nolink nlid="nl21" bibid="bib15" firstref="ref34"></nolink> <nolink nlid="nl22" bibid="bib18" firstref="ref35"></nolink> <nolink nlid="nl23" bibid="bib19" firstref="ref36"></nolink> <nolink nlid="nl24" bibid="bib20" firstref="ref37"></nolink> <nolink nlid="nl25" bibid="bib21" firstref="ref47"></nolink>
Header DbId: eric
DbLabel: ERIC
An: EJ1442252
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Do Schools That Employ an Inspector Get Better Inspection Grades?
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Christian+Bokhove%22">Christian Bokhove</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-4860-8723">0000-0002-4860-8723</externalLink>)<br /><searchLink fieldCode="AR" term="%22John+Jerrim%22">John Jerrim</searchLink><br /><searchLink fieldCode="AR" term="%22Sam+Sims%22">Sam Sims</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22British+Educational+Research+Journal%22"><i>British Educational Research Journal</i></searchLink>. 2024 50(5):2383-2406.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 24
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2024
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Inspection%22">Inspection</searchLink><br /><searchLink fieldCode="DE" term="%22Institutional+Evaluation%22">Institutional Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Leaders%22">Leaders</searchLink><br /><searchLink fieldCode="DE" term="%22School+Administration%22">School Administration</searchLink><br /><searchLink fieldCode="DE" term="%22Employment%22">Employment</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22United+Kingdom+%28England%29%22">United Kingdom (England)</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1002/berj.4025
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0141-1926<br />1469-3518
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In England, a substantial proportion of school inspections are conducted by current school leaders. This may lead to concerns that this gives their school (about 2% of schools) an advantage in the inspection process when it is their turn to be inspected. Yet scant evidence exists on this issue. This paper thus presents the first evidence on this matter, using data obtained via a freedom of information request and linking this with other publicly available information about England's schools. We find that schools where a member of staff also works for Ofsted receive better inspection outcomes than schools without an inspector on their payroll. Our findings nevertheless suggest that other schools may benefit from having access to the training material and professional development opportunities Ofsted provides to its inspectors.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2024
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1442252
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1442252
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1002/berj.4025
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 24
        StartPage: 2383
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Inspection
        Type: general
      – SubjectFull: Institutional Evaluation
        Type: general
      – SubjectFull: Leaders
        Type: general
      – SubjectFull: School Administration
        Type: general
      – SubjectFull: Employment
        Type: general
      – SubjectFull: United Kingdom (England)
        Type: general
    Titles:
      – TitleFull: Do Schools That Employ an Inspector Get Better Inspection Grades?
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Christian Bokhove
      – PersonEntity:
          Name:
            NameFull: John Jerrim
      – PersonEntity:
          Name:
            NameFull: Sam Sims
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 10
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 0141-1926
            – Type: issn-electronic
              Value: 1469-3518
          Numbering:
            – Type: volume
              Value: 50
            – Type: issue
              Value: 5
          Titles:
            – TitleFull: British Educational Research Journal
              Type: main
ResultId 1