Personality traits of municipal politicians and staff
Bibliographic record
Abstract
Abstract: Conflict between elected officials and civil servants is not an uncommon occurrence at the city level and it may at times paralyze the organization. The purpose of this article is to determine whether certain basic personality traits among municipal politicians and public servants could explain why the two groups have differing perspectives and why they may at times have difficulty working together. While they can be a source of considerable tension, these differing traits can also be seen as complementary, in which case they might enhance the organization's performance. Sommaire: Les conflits entre les responsables élus et les fonctionnaires ne sont pas quelque chose de rare à l'échelle des villes et ils peuvent parfois paralyser l'organisme. L'objet du présent article est de déterminer si certains traits de personnalité chez les responsables politiques municipaux et les fonctionnaires pourraient expliquer pourquoi les deux groupes ont des perspectives différentes et pourquoi ils peuvent parfois avoir des difficultés à collaborer. Alors qu'ils peuvent être une source de tension considérable, ces différents traits de personnalité peuvent aussi être considérés comme complémentaires et, dans ce cas, ils pourraient renforcer la performance de l'organisme.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".