SEX DIFFERENCES IN DATING ORIENTATIONS: SOME COMPARISONS AND RECENT OBSERVATIONS
Bibliographic record
Abstract
This study of 679 social science students in an Ontario university attempts to up grade and retest some of the notions in the literature about male-female relations in dating. Specifically, the approaches of Walter, Lowrie, and Burgess and Wallin were tested in this sample using semantic-differential items. Dating experiences for these students were positive and reflected values and experiences consonant with current beliefs; females were close to males in scoring their dating as sexual and hedonistic, while the general pattern involved high ratings of dating as pleasant, educational, cooperative and growth oriented. Inexperienced daters saw their dating as more positive than experienced daters. For most in the sample, dating was an end in itself and was not status or competition exploitation oriented—at least for the most part, even though these elements have not notably disappeared. Males were seen as less often cooperative in dating than females, while men registered more feelings of exploitation. While few of the respondents rated their dating as sexually aloof (less than ten percent), men were seen as too sex-oriented and women as immature. Men less often perceive their dating experiences as growth oriented while women see men as more crude and less often genteel. The relatively heavy emphasis on sensuatity and sexuality by both males and females is seen as indicating some change in dating patterns.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".