Gendered dating messages have consequences for both intended and unintended audiences
Bibliographic record
Abstract
Would-be-daters are surrounded by media messages that both target one gender and pit men and women against each other in the dating game (i.e., gendered relationship messages). How do these messages influence relationship initiation? In the present research, we focus on the consequences of being primed with gendered dating messages via actual book titles. We propose that such messages should have mixed consequences depending on (a) whether the reader’s gender is congruent with the message’s target gender and (b) the dating outcome. In two experiments, we tested how exposure to gendered dating messages influences emotions, motivation, and self-presentation. Individuals exposed to gender-incongruent messages exhibited higher self-protection motives. Conversely, those exposed to gender-congruent messages experienced reduced feelings of vulnerability, yet had the counterproductive consequence of creating less likeable self-presentations. Would-be-daters should be cautious in their exposure to both gender-congruent and gender-incongruent dating messages.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".