Organizational citizenship behavior: a case study of culture, leadership and trust
Bibliographic record
Abstract
The case will test two hypotheses regarding three variables influencing the level of employee satisfaction and organizational citizenship at GAMMA, a manufacturer of plastics. Two hypotheses were developed from a review of the literature and initial results from exploratory research ( H1 : low employee satisfaction at GAMMA is a direct result of an autocratic leadership style, low trust environment and weak corporate culture; H2 : low employee citizenship is a direct result of low employee satisfaction). Results suggest that although the perception was that employee satisfaction and organizational citizenship were low (from the exploratory research); both quantitative and descriptive data indicated these were not. Moreover, the hypotheses were not conclusively supported quantitatively. High trust was not obtained. Also a specific high leadership style and a specific culture resulting in high employee satisfaction were also questionable. Moreover, it was not observed that a strong correlation existed statistically. H1 is therefore not conclusive quantitatively. H2 does not demonstrate a high level of employee citizenship and employee satisfaction correlation. Despite these results, it is recommended management employ the following action plan: do not change current leadership style; develop an action plan to increase trust starting with increasing accessibility of management to employees; develop an action plan to move from current culture to preferred expressed culture starting by rewarding team activity rather than individual activities; improve employee satisfaction even if the observed level is medium to high.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".