Hallie Flanagan and the federal theater project: a critical undoing of management history
Bibliographic record
Abstract
Purpose This paper aims to accomplish two things: to build on current research which interrogates the role of management history in the neglect of women leaders and labor programs and to draw attention to Hallie Flanagan and the Federal Theater Project and their lost contributions to management and organizational studies. Design/methodology/approach This paper adopts a feminist poststructural lens fused with critical discourse analysis to capture the role of discourses in concealing a more fragmented view of history. Findings The findings are openly discursive and aim to disrupt current knowledge and thinking in the practice of making history. The paper calls for an undoing of history and an examination of the powerful forces, which result in a gendered and limited understanding of the past. Originality/value The objective of this paper is to help scholarship continue to transform management and organizational studies and management history and to raise the profile of remarkable leaders, like Flanagan and similarly remarkable programs like the Federal Theater Project. Flanagan managed arguably the most ambitious and novel labor program under the New Deal, which resulted in an average of 10,000 workers in the arts being employed over four years, in a project which engaged audiences of over 30,000,000 Americans.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.032 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".