Profit Sharing and Workplace Productivity Growth in Canada: Does Teamwork Play a Role?
Bibliographic record
Abstract
The purpose of this study is to contribute to knowledge of profit-sharing by utilizing a before-and-after analysis of panel data to assess whether the effects of profit-sharing adoption on productivity growth vary, depending on whether a profit-sharing adopter utilizes work teams or not, while controlling for numerous variables that may affect these results within a carefully constructed sample of Canadian establishments. To our knowledge, this is the first study to examine the moderating role of teamwork in the relationship between profit-sharing and productivity growth. Besides the implications for profit-sharing, ascertaining whether profit-sharing and work teams are complementary practices would have important implications for understanding how to develop more effective work teams, a topic of ongoing interest. We utilized a longitudinal research design to compare within-firm productivity growth during the three-year and five-year periods subsequent to profit-sharing adoption and within-firm productivity growth during the same periods in firms that had not adopted profit-sharing. Overall, our results suggest that use of team-based production plays an important moderating role in the success of employee profit-sharing—at least in terms of workplace productivity growth. Establishments that had adopted profit-sharing showed a substantial and highly significant increase in workplace productivity over both the three-year and five-year periods subsequent to adoption, but only if they had work teams. These findings are in line with the notion that work teams help to mitigate potential shirking behaviour in profit-sharing firms (Freeman, Kruse and Blasi, 2010) and are also in line with the argument that work teams serve as an effective mechanism to help translate the purported motivational and other benefits of profit-sharing into tangible productivity gains (Heywood and Jirjahn, 2009).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".