The Impact of Teaching Political Science on Political Awareness
Bibliographic record
Abstract
The study aimed at identifying the impact of teaching political science on the political consciousness of Petra University students, and to answer the study questions, a sample of the 131 students was selected, those enrolled in three sections in the first quarter of the academic year 2012/2013,a questionnaire was developed to collect information;it was built of 30 paragraphs and distributed , but only 87 of these were valid and analyzed. Results showed that the degree of political awareness among students was high with a mean of (3.70), in addition to the presence of statistically significant differences in the degree of impact of teaching political science on the political awareness of those students from their point of view, in terms of the gender variable, while no statistically significant differences appeared in terms of faculty, nor in terms of the variable grade point average –GPA. In the light of the results, the study recommended further studies on the subject, in order to disseminate the teaching of politics to be included in all universities that do not teach or enlist this topic within their programs. Key words: political awareness, the principles of political science, political participation, political education. 1.
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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 | 0.002 | 0.011 |
| 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 | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".