Some Good News, More Bad News: Two Decades of the Gender Pay Gap for Nonprofit Directors and Chief Financial Officers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This research examines differences in the compensation of male and female executive directors and chief financial officers in nonprofit organizations. We utilize executive transition periods within organizations as an empirical strategy for isolating how gender impacts the salaries of two people who occupy the same role in the same organization. Two waves of IRS 990 compensation data are used to assess compensation practices over the past two decades. The good news includes an overall increase in the number of women holding executive positions and indications that the discriminatory component of pay (discrepancies for two people holding the same position within the same organization) is relatively small and may be decreasing. This good news, however, is accompanied by bad news: large cross-sectional gaps in pay that result from an over-representation of male executives in the largest nonprofits and those in industries with the highest executive pay.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it