Examination of Attitude Levels of Academic Personnel Towards Political Participation and Determination of Its Relationships with Organizational Commitment
Bibliographic record
Abstract
The aim of this study was to determine the attitudes of academic personnel working in faculties of sports sciences in universities towards political participation; to examine whether there was a significant difference between the attitudes of academicians towards political participation according to demographic characteristics; to determine the relationships between academic personnel’s attitudes towards political participation and their organizational commitment. The study, which was designed in the correlational survey model of the general survey models, was carried out together with 204 academicians working in universities in Central Anatolia Region. The data of the study were collected by means of using the Political Participation Scale and Organizational Commitment Scale. Descriptive statistics, difference tests and Pearson correlation coefficient were used in the process of data analysis. At the result of the research, it was determined that the feelings of political activity and the feelings of alienation of academic personnel as well as their political perceptions arising from the institution were generally at a medium level. It was determined that there was a positive relationship between the feelings of political activity and the dimensions of organizational commitment of academicians.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".