Don’t just stand by!: speech act and politeness analyses of advice offered to a workplace bullying bystander in a public online forum
Bibliographic record
Abstract
Substantial research literature examines the processes surrounding workplace bullying, and bystanders are an integral component of this phenomenon. Many people also seek in-person or online advice when witnessing such deleterious events. However, research indicates that workplace bullying advice often becomes problematic. This study applied speech act and politeness analyses to examine how interlocutors in an online forum provided advice to a workplace bullying bystander. The analyses revealed that comments used speech acts that informed about personal experiences of workplace bullying and made claims about bullying in general that violated positive-politeness (i.e. sense of belonging) most often. This study also found that messages providing clear directions (i.e. direct speech acts) for the bystander disproportionately violated negative-politeness (i.e. personal autonomy). This study extends our knowledge of workplace bullying advice to include structural markers such as speech acts and politeness strategies. Using insights from this study, organizational professionals can develop bystander intervention strategies using direct speech acts coupled with positive- and negative-politeness observations to mitigate workplace bullying issues.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".