Why Are You Bringing Up Condoms Now? The Effect of Message Content on Framing Effects of Condom Use Messages.
Bibliographic record
Abstract
According to prospect theory (A. Tversky & D. Kahneman, 1981), messages advocating a low-risk (i.e., easy, low-cost) behavior are most effective if they stress the benefits of adherence (gain framed), whereas messages advocating a risky behavior are most effective if they stress the costs of nonadherence (loss framed). Although condom use is viewed as a low-risk behavior, it may entail risky interpersonal negotiations. Study 1 (N = 167) compared ratings of condom use messages advocating relational behaviors (e.g., discussing condoms) or health behaviors (e.g., carrying condoms). As predicted, loss-framed relational messages and gain-framed health messages received higher evaluations. Study 2 (N = 225) offers a replication and evidence of issue involvement and gender as moderators. Results are discussed with reference to the design of condom use 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 | 0.010 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".