The insider view: tackling disabling practices in higher education institutions.
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| Title: | The insider view: tackling disabling practices in higher education institutions. |
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| Authors: | Merchant, Wendy1, Read, Stuart2, D'Evelyn, Stephen3, Miles, Caroline4, Williams, Val3 val.williams@bristol.ac.uk |
| Source: | Higher Education (00181560). Aug2020, Vol. 80 Issue 2, p273-287. 15p. 1 Chart. |
| Subject Terms: | *Universities & colleges, *Ableism, *People with disabilities, Income, Equality |
| Abstract: | This paper reports on research about the experiences of disabled staff members in UK universities, drawing on eleven semi-structured interviews with disabled staff in one university, alongside a group auto ethnography conducted by the first four authors, all of whom identified as disabled academics. Disability is generally considered to be predominantly an issue for students, both in practice and in the literature. By contrast, taking a social practice approach, we focused on the barriers faced by disabled employees, both overt and hidden. We found that disability was still viewed as a medical problem, and that disabled members of staff faced considerable extra labour in organising their own supports. We were often made to feel that we were unwanted and that we were 'misfits' in the institution. This paper contributes to theory by showing how social practices can become exclusionary, and how interconnections between practices matter. We discuss ways in which ableism, based on the ideal of 'individual' excellence, creates barriers for disabled staff. In the global context of Higher Education, the increasing marketization of universities in higher income countries creates a difficult climate for the values of inclusion. [ABSTRACT FROM AUTHOR] |
| Copyright of Higher Education (00181560) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
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