Teaching relationship science: Continuity and change in the craft
Bibliographic record
Abstract
Abstract Relationship science is a dynamic, flourishing enterprise, with numerous discoveries and new lines of inquiry evident in recent changes in its textbooks and the teaching activities invented by its instructors. To survey changes and challenges in the teaching of courses that introduce students to relationship science—and to pursue “news instructors can use”—we surveyed 135 instructors of relationships courses regarding their teaching tactics and experiences. Guided by their responses and suggestions for further inquiry, we also examined the changes in textbooks on which they rely and reviewed teaching activities created to assist them with their teaching over the last 20 years. At present, some topics are nearly universal components of relationships courses but idiosyncrasy exists, particularly with regard to new topics—such as coverage of technology , intersectionality , or consensual nonmonogamy —that instructors plan to include in revisions of their courses. Suggestions for both new and experienced instructors are provided.
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How this classification was reachedexpand
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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".