Bibliographic record
Abstract
This exploratory research analyses the careers, teaching practices, and self-assessments of Ontario college media teachers in three parts of the Province and three time periods (those hired in the 1970s and 1980s, 1990–2007, and 2007–2022). I interviewed 15 retired media teachers and academic managers; also, 42 current instructors and academic managers answered a survey about their professional experiences. My analysis uses a feminist model of closure theory from the neo-Weberian sociology of professions (Witz, 1992) along with intersectional writing on identity to explain the gendered and racialised nature of the labour market in these geographically and historically specific areas and eras. At the beginning of the first period, privileged white middle-class men with connections to education and industry experience founded the programmes, eventually hiring privileged white women with relevant credentials, all teaching full-time. In the 1990s, the neoliberal practice of hiring substantial cohorts of non-fulltime (NFT) teachers, and a demand for graduate university credentials can be linked to the advent of joint university-college media programmes and an increase in hiring of administrative staff (Mackay, 2014). In the programmes themselves, I found that the institutionalised apprenticeship model of the early college changed to a skills-based curriculum, the current emphasis in all college programmes. In hiring, gender parity for white heterosexual women has been achieved in the central hub, and consciousness of race has grown over time. However, media teachers still do not match the intersectional diversity of their students due to credentialist and legislative professional closure in hiring and promotion among fulltimers. I theorise that this closure operates by requiring credentials for full-time positions that are not available to all, depending on intersectional class, race, sexuality, disability, neurodiversity, and age.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".