O<scp>rganizing at the</scp> M<scp>argins</scp>: W<scp>omen</scp> S<scp>hape the</scp> L<scp>abor</scp> M<scp>ovement</scp>
Bibliographic record
Abstract
It is frequently the case in social change movements that women organize on the margins, performing labor that is often invisible but indispensible to the movement's growth and success.One of the more significant developments in the field of labor studies over the last three decades has been the effort to document this often-invisible labor.Historians such as Ava Baron, Annelise Orleck, Dorothy Sue Cobble, and Alice Kessler-Harris (whose most recent book is reviewed in this issue) have argued for women's workplace activism as creating a distinctly working-class feminism that has significance for both the feminist movement and the labor movement.1 Their work-as well as important work in the fields of anthropology, sociology, women's studies, political science, and literary and cultural studies-has helped demonstrate the necessity of viewing Labor Studies through the lens of gender. 2 Such works make the case for the importance of acknowledging both women's experiences and of the role of gender as shaping forces in the workplace and the labor movement, both in the United States and globally.The essays in this issue are a powerful call to make women's labor activism visible and to recognize the ways that their activism can help shape the labor movement as a whole.Most of them address issues that have been raised in other essays about women workers: the gender gap in specific industries and organizations, the wage gap, the struggle to maintain a work-family balance, and the prevalence of sexual discrimination and harassment in the workplace.However, many of these essays provide particular insight into ways women workers organize and effect change in the workplace by drawing on their kinship and community networks.3 Together, these essays suggest that women's activism and leadership not only improve women's working lives but also benefit the labor movement as a whole by contributing to a more democratic and workercentered social justice movement.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.098 | 0.031 |
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".