Relationship between Spiritual Leadership and Organizational Commitment in Malaysians’ Oil and Gas Industry
Bibliographic record
Abstract
The study attempts to fill in the empirical gap of spiritual leadership relationship with organizational commitment in the oil and gas industry in Malaysia. On a wider perspective, the study will provide an insight on spiritual leadership adoption in the oil and gas industry and how well it has contributed to the overall efficiency towards productivity and growth. The effectiveness of a particular leadership approach may differ from one industry to another based on the demographic, geographic or principle of business factors. In an attempt to get an adequate and good generalization, out of approximately 106,000 populations, 203 respondents were selected from 11 main subgroups: namely the oil and gas related firms operating within the gazetted industrialed zone by using quota sampling. Relying on four constructs measuring spiritual leadership the investigation hypothesized their relationship with the committment at work. The findings of the research may serve as a reference for organizations to make decisions on the leadership approach that suits with the organizational environment. Similar studies on the context of spiritual leadership conducted by researchers around the world have been sparse due to the fact that the implementation of such approach is still at its infancy. Therefore, the findings from the study are important to contribute to the academic literatures as well as to provide enrichment in the discussion of the subject matter.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".