When is an Islamic work ethic more likely to spur helping behavior? The roles of despotic leadership and gender
Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate how employees’ Islamic work ethic might enhance their propensity to help their coworkers on a voluntary basis, as well as how this relationship might be invigorated by despotic leadership. It also considers how the invigorating role of despotic leadership might depend on employees’ gender. Design/methodology/approach Survey data were collected from employees and their supervisors in Pakistani organizations. Findings Islamic work values relate positively to helping behaviors, and this relationship is stronger when employees experience despotic leadership, because their values motivate them to protect their colleagues against the hardships created by such leadership. This triggering role of despotic leadership is particularly strong among female employees. Practical implications For organizations, the results demonstrate that Islamic work values may be important for creating a culture that promotes collegiality, to a greater extent when employees believe that their leaders act as despots who exploit their followers for personal gain. Originality/value This study elaborates how employees’ Islamic work ethic influences the likelihood that they help their coworkers, particularly in work contexts marked by stress-inducing leadership.
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 | 0.003 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".