Affirmative sexual consent? Direct and unambiguous consent is rarely included in discussions of recent sexual interactions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sexual activity typically follows an implicit sexual script or a normative sequence of behaviours that are involved in a sexual interaction. It is unclear whether or how affirmative sexual consent is incorporated in individual sexual scripts and interactions. The current research explores how sexual consent may be expressed and verified as part of individuals’ sexual interactions. Undergraduate participants from an Ontario university ( N = 92; 58 males, 34 females) completed a series of open-ended questions that asked them to describe their sexual experiences with a new and long-term partner from beginning to end. Analysis of presence of consent-related behaviours in participants’ accounts were assessed on the basis of a priori themes and extensions of these themes. Thematic analyses identified the following themes: 1) Sex proceeding with escalating intensity of nonverbal sexual behaviour, 2) Passive behaviours that do not indicate unwillingness to have sex, 3) Indirect verbal communication of interest in sex, 4) Indications that sex “just happened,” 5) Descriptions of the context in which sex occurred, and 6) Direct discussions relevant to sexual consent. Results indicated that direct discussion of sexual consent was exceedingly rare and that most sexual interactions included indirect, veiled, and coded behaviours that require inference of sexual consent or non-consent. Consent-related themes varied as a function of both participant gender (male versus female) and nature of relationship (new versus long-term). The findings of this study have implications for sexual health education, sexual assault prevention interventions, and public policy development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it