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Supporting data for "University governance and academic work in a neoliberal landscape of higher education: Preparation for Research Assessment Exercise (RAE) 2020 in Hong Kong"

dataset
posted on 2021-06-24, 07:18 authored by Danling Li
Interview data with 16 RAE-eligible academics in Social Sciences and Education from two UGC-funded universities in Hong Kong

Participants: A purposive snowballing sampling approach was adopted to invite sixteen RAE-eligible academic staff at Institutions A and B. These participants were at different academic stages (seven professors, three associate professors and six assistant professors). Seven had experiences in managing the RAE exercises and performed different administrative duties, e.g., research governance, knowledge transfer activities, faculty/department management.

Data collection procedure: After receiving ethical approval from the university, I conducted semi-structured and text-based interviews with the 16 participants individually from October 2019 to October 2020, immediately after the census date for RAE 2020 in Hong Kong (30 September 2019). The participants’ academic profile and research publications, retrieved from their official websites, were studied in advance before the interview. During each individual interview, I would first briefly illustrate the focus of my Ph.D. project and the topic areas that would be covered in the interview questions. The participants were also encouraged to elaborate on any information they feel appropriate. English or Mandarin Chinese was used during the face-to-face interviews. For the interviews conducted in Chinese, English words and phrases (e.g., “3*/4*”, “SSCI”) were frequently used. The length of each individual interview ranged from 40 minutes to 70 minutes, with the average length being around 60 minutes. Interviews were conducted and audio-recorded with informed consent. Compensation was provided to appreciate their collaboration and support, upon their completion of the interviews.

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