Gender, ethnicity, and career trajectories: A comment on Woodward (2010).
Bibliographic record
Abstract
Woodward (2010) argued that Maria Rickers-Ovsiankina, Eugenia Hanfmann, and Tamara Dembo constituted a group of Jewish emigré psychologists who received substantial help in America from a "Jewish network" of patronage. This comment focuses on the historiographic problems and pitfalls of essentialized ethnic identification. There was no evidence that Maria Rickers-Ovsiankina was a Jew or that Eugenia Hanffman, raised Russian Orthodox, identified herself as a Jew, in contrast to Tamara Dembo, who did so. We argue that these women were part of an active network of Gestaltists, topologists, and Society for the Psychological Study of Social Issues leaders, and that any help that they received may be explained by the shared theoretical and disciplinary outlook of these groups as opposed to a "Jewish network."
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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.055 | 0.044 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".