Psychology of Women and the Potential for Influencing Students' Lives: An Interview with Margaret W. Matlin
Bibliographic record
Abstract
Lori Van Wallendael is an associate professor of Psychology and coordinator of the Women's Studies program at the University of North Carolina at Charlotte. She teaches courses in psychology of women, general psychology, cognitive science, history and systems of psychology, research methods, and psychology and law, among others. Her research interests include human decision making, eyewitness and earwitness memory, and juror intuitions about memory issues. Margaret W. Matlin is a distinguished teaching professor at SUNY Geneseo. She is a Fellow of the American Psychological Association, the American Psychological Society, and the Canadian Psychological Association. During her teaching career, she has been the recipient of the SUNY Chancellor's Award for Excellence in Teaching, the Society for the Teaching of Psychology (Division 2) Award, and the American Psychological Foundation's Distinguished Teaching in Psychology Award. She is the author of Cognition (5th ed., 2001), The Psychology of Women (4th ed., 2000), Psychology (3rd ed., 1999), and the coauthor (with Hugh Foley) of Sensation and Perception (4th ed., 1997). She has also authored or coauthored 21 instructor's manuals, student study guides, and test-item files as well as 8 chapters in books and 45 published articles.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".