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
Purpose This exploratory study examined backlash in the workplace. Backlash was operationalized by employee views on how much their employer had done to support the advancement of four designated groups (women, disabled, aboriginal people, racial/visible minorities): too much, about right, too little. Design/methodology/approach Data were collected from 2,514 employees of a single financial services organization (1,962 women, 480 men) using anonymous questionnaires. Findings The majority of the sample thought their employer had done about the right amount. Women thought the firm had done less for women than men did; men thought the firm had done less for aboriginals than women did. Males more strongly endorsing backlash had longer company tenure and tended to be at lower organizational levels. Women and men endorsing backlash were then compared on a variety of work and organizational outcomes. Men believing the firm had done too much, and women believing the firm had done too little generally indicated less satisfying work and organizational outcomes. Research limitations/implications Study needs to be replicated in other organizations using a different measure of backlash. Practical implications Suggestions for dealing with backlash are offered. Originality/value Examines a relatively important but under‐researched subject.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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