Supporting part-time teachers and contract faculty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Unprecedented increase in access to higher education over the past decade, particularly in the UK and Canada has required Higher Education Institutions (HEIs) to employ more instructors, increasingly on contractually limited arrangements. What began as a short-term solution has now become the norm in many countries. In some disciplines, for example professional and practice-based subjects, there is a history of employing staff/faculty on contractual basis, bringing valuable professional and industrial experience. Contextual pressures influence universities: changing expectations of their nature and purpose, the relationship between students and universities, changes in curriculum and teaching. At the same time, potential students and future employers scrutinise student satisfaction with the quality of their education. Public support for permanent/tenured positions has declined (Kezar, Maxey and Eaton 2014) and there is a demand for a more flexible workforce. These conceptual and practical considerations are crucial to effective support for part-time and contractual staff. This chapter includes a series of case studies and examples from the literature, intended to illuminate good practice in the support and development of these instructors.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it