The Study on Relationship between the Traits of Leaders and the Performance of the Leaders under Different Organizational Cultures
Bibliographic record
Abstract
Regarded leader’s traits as independent variables, performance as dependent variables, organizational culture as control variables, this paper found that under the innovation-orientation culture, the tuition type of perception type, risking-taking , and artistic subscale significantly and positively correlated with performance. Under the support-orientation culture, the affiliation motive and the ability of understanding diction have a significantly positive correlation with performance. Under rule-orientation culture, the power motive, the conventional subscale, and the ability of analyzing datum have a significantly positive correlation with performance. Thus, the hypothesis of the leader’s trait theories based on context proposed in this paper is validated. Key words: traits, organizational culture, leadership Resume: En considerant les traits de leaders comme variables independantes, la performance comme variable dependante, la culture organisationnelle comme variable de controle, l’article present trouve que, sous la culture d’innovation-orientation, le type de frais scolaires du type de perception, le risque-recette et le subscale artistique se rapportent significativement et categoriquement a la performance. Sous la culture de support-orientation, le motif d’affiliation et l’aptitude de comprehension du langage a une correlation evidente avec la performance. Sous la culture de regle-orientaion, la force motrice, le subscale conventionnel et la capacite d’analyse des donnees a un lien effectif avec la performance. Ce faisant, les hypotheses des theories de triats de leaders basees sur le contexte dans l’article s’averent fondees. Mots-Cles: traits, culture organisationnelle, direction
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".