More Than a Personal Decision: A Relational Theory of Quiet Quitting
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
ABSTRACT Quiet quitting first exploded in social media and has gained considerable traction in media, practitioner, and scholarly outlets. While much of this attention has been focused on why employees quiet quit, there has been less consideration about how it is perceived by their coworkers. Combining insights from relational climate and social networks scholarship, we develop a novel theory about its potential interpersonal consequences. Our theory elucidates how employee quiet quitting and coworker reactions will differ across market pricing, equality matching, and communal sharing climates. We propose that while harmonious relational climates will facilitate the most support from coworkers, these climates will also trigger the most harmful responses when quiet quitting does not eventually dissipate. We also theorize how the collective monitoring and reporting norms that typically develop within these climates will facilitate sanctions via collective forms of mistreatment, such as social undermining and ostracism. Not only does our theory extend the relevant consequences of quiet quitting to include interpersonal ones, but it also therefore explains how seemingly positive climates can inadvertently enable mistreatment. We outline the contributions of our theory to the growing literature on quiet quitting, suggest directions for future research, and offer implications for human resource management practitioners.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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