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A Career of Precarious Subservience and Silencing Within the Academy Across Canada

2025· book-chapter· en· W4413126537 on OpenAlexaboutno aff
Steven Noble

Bibliographic record

VenueAdvances in higher education and professional development book series · 2025
Typebook-chapter
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceSociology

Abstract

fetched live from OpenAlex

The notion of contract professors – variously called adjuncts, sessionals, visiting professors – has become such a common fixture in the academic landscape that they are given little notice. Students do not see the stark differences between someone “on the track” of tenure or fighting to survive contract to contract, mixed in with other short -term work in between teaching gigs. Living and working on the social edge, however, gives the author a clearer vantage from which to view how precarious professors get constructed by the tenure track and managerial centre of the modern, neoliberal post-secondary sector. The author has found himself moving across the country, from Vancouver Island to Halifax chasing contracts. To support this exploration, the author draws upon the tenets of critical theory and queer theory. This chapter contains a critical autoethnographical study of the author's time as a contract academic across four Canadian provinces in colleges and universities from 2005 to the present (20 years). Recommendations are provided that would further support the precariat.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.832
Threshold uncertainty score0.965

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0530.016
Scholarly communication0.0120.002
Open science0.0020.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.047
GPT teacher head0.383
Teacher spread0.336 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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