Bibliographic record
Abstract
Using the micro-data from Human Resources and Social Development Canada (HRSDC) on the 23,944 stoppages in Canada between 1960 and 2004, this article introduces a labour militancy perspective on work stoppages, that is, from the point of view of workers. It explores patterns of militancy with a focus on strike duration, strike size and strikes for first contracts, and supports re-interpretations which help make visible the significance of such stoppages for workers, unions and communities. A labour militancy frame presents an alternative to the employer perspective on time lost, the government concern to measure the economic impact of stoppages, and the scholarly emphasis on strike determinants. As part of re-examining the HRSDC work stoppage data from a labour militancy perspective, the paper considers the source of these data. It juxtaposes the statistical data with interviews with the provincial correspondents who collect the information for HRSDC. Examining the data in this light underscores the political nature of data collection (what is seen to be germane and not), data presentation (what is made visible and what is not), and data sources (whose voices are heard).
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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".