A Diagnostic Method for Procedural Justice
Bibliographic record
Abstract
Procedural justice has shown significant linkages to organizational outcomes such as organizational commitment and turnover. For this reason, we propose that measures of procedural justice can serve a diagnostic function to signal potential problems with important organizational-level outcomes. However, if used alone, it does not tell us which specific procedures require change in order to resolve potential problems. This study proposes, and tests, a methodology which combines general measures of procedural justice with measures of perceptions of specific procedures in order to diagnose problems with organizational outcomes. This is tested in two call centers. The research design employs a survey of randomly selected employees from the call centers. The effects of a general measure of procedural justice on the organizational outcomes of turnover intentions and organizational commitment are examined. Further, we examine the effects of attitudes towards specific monitoring procedures on a general measure of procedural justice. Baron and Kenny’s statistical methodology is employed to test these relationships; to show that procedural justice mediates the effect of employee perceptions of monitoring on turnover intentions and organizational commitment. Our findings support complete mediation effects. The implications of these findings are that general perceptions of procedural justice can be used to screen for potential problems with organizational outcomes. If general effects are found, organizations can employ more specific measures of organizational procedures to target procedural problems. The methodology proposed here has the potential to identify specific procedures that organizations can focus on in order to improve organizational outcomes. Normal 0 false false false EN-US X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:Table Normal; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; text-align:justify; mso-pagination:widow-orphan; font-size:11.0pt; font-family:Calibri,sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;}
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".