Organizational logic and feminist organizing: stewardesses for women's rights
Bibliographic record
Abstract
Purpose Joan Acker proposed her gendered theory of organization as a framework to analyze organizations and to understand how gender underlies organizational structure in such a way as to subordinate women. Much of the previous work that has utilized this framework has examined highly (male‐) gendered organizations. This archival case study aims to use Acker's framework to examine a purportedly female‐gendered organization – the 1970s feminist organization, Stewardesses for Women's Rights (SFWR). Design/methodology/approach Using these archived materials, this paper uses a critical hermeneutic approach across Acker's framework of gendered organization to make sense of the rise and fall of SFWR. The paper discusses lessons learned from this short‐lived organization. Findings The paper finds that societal pressure and organizing women's understanding of what is “real” and valued in an organization pushed them to create an organization that was as highly (male) gendered as the organizations from which they were escaping. Many in the organization never saw SFWR as a “real” organization because of the underlying organizational logic that was directing what the organization should be. Even if the organization did, on the surface, look different than other explicitly male‐gendered organizations, the same underlying organizational logic manifested itself in similar organizational structure. Originality/value This archival case study uses Acker's framework to examine a purportedly female‐gendered organization – the 1970s feminist organization SFWR and reveals lessons learned.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.050 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".