Solidarity by Association: The Unionization of Faculty, Academic Librarians and Support Staff at Carleton University (1973-1976) Transcript [Vickers]
Bibliographic record
Abstract
Vickers speaks about her involvement in the certification of the Carleton University Academic Staff Association (CUASA) in the mid 1970s. She was the CUASA president from 1974 to 1975 and one of the leaders of the drive to create a union for faculty at Carleton. She describes the events leading up to the decision to certify and the challenges faced in overcoming opposition to unionization by academic staff who did not believe that unions were appropriate for them, as white-collar workers. She describes the context in which this significant shift in occupational status took place, including the gendered the nature of the university workplace. In particular, she talks about working conditions for female staff on campus—for faculty, librarians and support staff. Uncorrected transcript (approximately 16 p.) from the original audio tape. Number of sessions: 1 Length of interview: Approximately 40 minutes Place of interview: Carleton University Library, Ottawa, Ontario Date of interview: May 4, 2011 Language of interview: English Name of transcriber: Teevi Mackay Date of transcription: July - August, 2011 Software used for transcription: NVivo
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.014 |
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".