Three essays on customer interpersonal injustice and frontline employees’ corresponding attitudinal and behavioral outcomes
Bibliographic record
Abstract
Customer interpersonal injustice is a ubiquitous phenomenon that frontline employees often experience in the workplace.Nonetheless, only a limited number of studies have explored this phenomenon.In order to comprehensively explore customer interpersonal injustice and its outcomes, this dissertation presents three essays: the first will probe the various behavioral changes employees might manifest as a consequence of receiving chronic unfair treatment from customers (Essay one), the second will examine diverse types of mediating effects in the relationship between customer interpersonal injustice and turnover intention (Essay two), and the third will determine whether employees' personality traits and emotional state moderate the relationship between daily customer interpersonal injustice and employees' daily customerdirected sabotage (Essay three).Each essay offers enriching theoretical and practical implications for how frontline employees' perceptions of interpersonal unfairness from customers can affect employees' cognitive (e.g., moral outrage), behavioral (e.g., customer-Table of
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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 | 0.003 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".