Organizing Working-Class Academics: A Collective History
Bibliographic record
Abstract
In 2008, the Association of Working-Class Academics was founded in upstate New York by three former members of the Working-Class/Poverty-Class Academics Listserv. The Association had three goals: advocate for WCAs, build organizations on campuses that would support both working-class college students and WCAs, and support scholarship on issues relevant to class and higher education. The Association grew from a small handful to more than 200 members located in the US, UK, Australia, Canada, and Germany. In 2015, it was formally merged with the Working-Class Studies Association, and continues there as a special section for WCSA members. This is our collective account of the organization, told through responses to four key questions. We hope this history will provide insight and lessons for anyone interested in building similar organizations.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.034 | 0.030 |
| Scholarly communication | 0.023 | 0.012 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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".