Trade union intervention in workplace bullying: issues of employee voice and collectivism among union members and officials
Bibliographic record
Abstract
This study explores the role of trade unions in intervening in incidents of workplace bullying, adopting an employment relations perspective. The data was obtained from the members and officials of three major UK unions and analysed using both qualitative and quantitative techniques. Between a quarter and a third of respondents in each union considered they were bullied within a two-year period. A key finding was that most bullied individuals voiced their concerns through non-organisational support mechanisms, including trade unions, in preference to the systems created by employers to address bullying. Colleagues rarely offered overt support and union officials typically responded by providing indirect support to individual bullied members. Outcomes tended to place the onus on perceived targets of bullying to resolve the situation irrespective of the source of support utilised. Employers' attitudes towards bullying appeared to exert greater influence over resolutions. Whilst unions may have limited power to alter managerially-derived solutions, there was some evidence that, where they engendered a collective response to allegations of bullying, perpetrators were more likely to be held accountable. This study makes a significant contribution to the collective knowledge on workplace bullying by proposing a typology of union responses and an industrial relations model of intervention, which highlights the potential for the responses of unions, co-workers, and employers to affect the balance of power in the employment relationship and influence outcomes of work place problems like bullying.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".