AN APPROACH TO UNDERSTANDING LEADERSHIP DECISION MAKING IN ORGANIZATION
Bibliographic record
Abstract
This study examined the vital approach to understanding leadership decision making in organizational leadership and management activities. The purpose of this paper is focused and centered on the best approach to understanding the leadership decision making process (LDMP) among leaders and managers in organizational activities. This phenomenological qualitative paradigm which focused on essence or structure of an experience was used in order to gain in-depth knowledge and understanding of the issues and challenges affecting effectiveness, clarity, and success among organizational leadership and managements in business practices. Two hundred and sixteen organizational leaders from some cities and states in North America (Canada, Mexico, and United States) participated in this study and identified how they acquired their leadership role, knowledge, and skills. The findings from this investigation suggest that organizational leaders should allow their skilled subordinates - individuals and/or groups to participate in the decision making process mostly when their involvement will enhance the quality and/or acceptance of the decision by everybody at the workplace.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".