The work of university research administrators: Praxis and professionalization
Bibliographic record
Abstract
As part of a project on the social production of social science research, 19 research administrators (RAs) in five Canadian universities were interviewed about work, careers, and professionalization. While rarely featured in the higher education literature, RAs have become an important source of assistance to academics, who are increasingly expected to obtain and manage external research funding. RAs perform multiple roles, notably assisting with the complexities of grant-hunting as well as managing ethical clearance, knowledge mobilization, and related activities. Aspects normally associated with professionalization include organizations that control entry, higher degrees in the field, and clear career paths, all of which are somewhat compromised in the case of RAs. Nevertheless, most of the participants regard research administration as a profession, and we argue that it is more important to focus on the sensemaking and identity formation of these mostly female staff than to apply abstract criteria. Although their efforts do little to challenge a culture of performativity in the academy, and indeed may be regarded as supporting it, the RAs have defined for themselves a praxis dedicated to easing the burdens of the academics, helping one another, and contributing to the greater good of the university and the research enterprise.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.072 | 0.095 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.032 | 0.046 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".