Bibliographic record
Abstract
Purpose – The purpose of this paper, building on the work of Aubéet al.(2009, 2011) who developed a four-dimension model of counterproductive behaviors in team settings, is to examine the team-level consequences of these behaviors. More specifically, the authors investigate the mediating role of collaboration, a key component of teamwork, in the counterproductive behaviors–team performance relationships. Design/methodology/approach – Using a multisource approach and a team-level design, data were gathered from 101 work teams (381 members and 101 immediate supervisors). The study was conducted within a Canadian public safety organization. Findings – Results show that the four dimensions of counterproductive behaviors are negatively related to team performance. Moreover, results indicate that each of these relationships is completely mediated by a decrease of collaboration among members. Taken together, the results of this study show that the presence of counterproductive behaviors within teams constitutes a collective phenomenon which affects not only team members, but also the functioning and effectiveness of the team as a whole. Originality/value – This study differs from previous studies mainly by adopting a multidimensional conception of counterproductive behaviors and focusing on consequences of these behaviors on the team as a system. In practical terms, the results suggest that the presence of counterproductive behaviors may require team-level interventions (e.g. team building) in addition to individual interventions with individuals involved.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".