Bibliographic record
Abstract
Students on university campuses are having sexual experiences that seem to be different than sexual experiences of students of previous generations. Traditional “going steady”, committed relationships are being challenged by a pervasive casual sex culture across university campuses (Allen, 2004). Among students and in the media, this culture of casual sex is often referred to as “hookup culture.” Media commentary often presents hookup culture as a sign of negative moral change. I am interested in seeing if there is another side to this argument. I will use student perspective on this hookup culture to identify whether men and women understand this culture differently, and look at hooking up as a source of empowerment. To focus my study, I will look at the phenomenon colloquially know as the “walk of shame” as a way to represent the sexual hook up culture here at Queen’s. I will conduct 2-3 focus groups with a total of 7-10 female and 2-5 male participants. The participants in this study will be self-identifiedheterosexual students who also identify themselves as participants in hookup culture, currently enrolled in undergraduate studies at Queen’s University. Although literature has examined hookup culture among various populations, my research will examine how heterosexual students perceive the sexual culture here at Queen’s. I expect these discussions to offer commentary on hookup culture from a first hand perspective. This study will contribute to the to Queen’s students’ existing knowledge about their ownsexual culture, but also provide insight for non-student members of the Queen’s community.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".