Detecting the Gender Dimension of the Choice of the Teaching Profession Prior to the Economic Crisis and IMF (International Monetary Fund) Memorandum in Greece-A Case Study
Bibliographic record
Abstract
The purpose of this research paper is the investigation of , and the sociological approach to, and interpretation of the attitudes of male and female students in the University Department of Primary Education (U.D.P.E.) at the University of Patras in Greece, before the enforcement of the IMF Memorandum, concerning the choice of the teaching profession and the corresponding scientific field of studies. In particular, we will be concerned with the following research questions: a) what are the attitudes of male and female students regarding the reasons for the choice of the particular scientific field and b) What is the influence of the gender of the male and female students of the U.D.P.E. at the University of Patras as far as the choice of studies in the particular scientific field is concerned. The most significant findings of the work reveal that in the particular University Department female students are overrepresented in percentage terms, a fact which demonstrates the ‘feminizing’ of the Department in question. It also became apparent that the educational and professional choice of the female students in the particular University department is guided by their gender, which directs their practice. Finally, the prospect of immediate and certain professional employment which studies in the field of teaching in Greece promised, before the appearance of the economic crisis and the enforcement of the austerity measures, emerged as the most significant factor in the choice of the teaching profession by both sexes.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".