Gigification of English Language Instructor Work in Higher Education: Precarious Employment and Magic Time
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
Abstract This article describes how discourses of professionalism, insecurity, and exploitation among English as a second language/English for Academic Purposes (hereinafter ESL/EAP) instructors and curriculum‐level administrators at two Canadian universities relate to their understanding of fair work. These understandings are examined in a nested manner, in keeping with social positioning theory. Via discourse and thematic analysis of job advertisements and semi‐structured interviews, we illuminate aspects of the gigification of ESL/EAP in Canada, wherein ESL/EAP instructor work is increasingly rendered un(der)paid, constantly evaluated, surveilled, and precarious. Viewed through the lens of “magic time,” an infinite category of work time, we document the frustrations of ESL/EAP instructors who recognize their own exploitation. The relevance of this study is described in relation to the growing numbers of international students at English‐speaking universities throughout the world requiring a robust program infrastructure supporting their success, while the ESL/EAP instructors who provide these programs are increasingly made disposable through contingent employment relationships. The increasing reliance on contract professors teaching for‐credit courses in higher education has come to be known as adjunctification. In the noncredit, the more marginal context of ESL/EAP instructors subject to the forces of international student supply and demand, underpaid even by contract faculty standards, and engaged in often cutthroat competition for the few remaining contracts, we reference contextual differences by calling it gigification.
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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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