Worker Voice and Mutual Gains From Remote Performance Management: Evidence From Digitalized Services in North America and Germany
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 The expansion of remote working arrangements has required managers to adjust their approach to managing performance, as they transition from in‐person to technology‐mediated tools and practices. Past research has identified negative worker impacts associated with intensified digital monitoring and discipline‐based coaching. However, few studies have investigated the antecedents of more worker‐friendly arrangements. This paper examines the role of collective worker voice in shaping remote work performance management choices, based on a comparative study of telecommunications call centers in Canada, the United States, and Germany. Findings suggest that strong collective voice, especially when backed by institutional power, fosters a balanced approach to remote performance management by constraining the intensity of electronic performance monitoring and use of disciplinary practices, as well as by supporting more developmental coaching.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it