Bibliographic record
Abstract
80 romantic couples (N = 160) from the San Francisco Bay Area (including UC Berkeley students) enrolled in a study with: (1) baseline survey measures, (2) lab interactions (sacrifice, suffering, and love), (3) a 14-day daily experience study and (4) a three-month longitudinal follow-up survey. To be eligible, they must have been at least 18 years old and in a romantic relationship for a minimum of 6 months. On average, participants were in their mid 20s (range 18-60), had been involved in their romantic relationship for a medium length of 15 months, 53% were European or European American, and 75 out of the 80s couples were heterosexual. Participants independently completed a 45-minute online questionnaire in the days prior to their first lab session. The couple attended the lab session together. There, the participants participated in a series of structured videorecorded conversations, and privately answered brief questionnaires after each conversation. Topics were: - A major sacrifice they had made for their partner over the course of their relationship (sacrifice conversation). - A disclosure of a time of personal suffering (suffering conversation). - A time when they had experience a great deal of love for their partner (love conversation) For the subsequent two weeks (14 nights), couple-members independently completed a brief nightly questionnaire about their day (including personal well-being and interactions with the partner, with many questions about daily sacrifices). Three months after the completion of the diary part of the study, both partners separately completed a longitudinal follow-up survey with questions about their relationships. Participants in this study also provided saliva samples that were used for genotyping. This study was approved by the University of California, Berkeley Institutional Review Board (ethics number not known)
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.007 |
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".