When unfairness matters most: supervisory violations of electronic monitoring practices
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 study examined the effects of different sources of monitoring information, quality of treatment and quality of decision‐making manipulations on perceptions of fairness and satisfaction with monitoring. Drawing on Blader and Tyler's four‐component model of fairness, participants were asked to rate their perceptions of fairness, satisfaction and intentions to comply with electronic performance‐monitoring policies that originated from formal organisational policies or from their direct supervisors. Results indicated that procedural justice violations originating from the supervisor (vs. formal organisational policy) led to lower perceptions of fairness and satisfaction with monitoring. Furthermore, the effect of procedural justice violations on compliance with monitoring was mediated by perceptions of fairness and satisfaction with monitoring. The present research has theoretical and practical implications for the design, implementation and communication of organisational electronic monitoring practices.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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