EDRA Archives donated by John Zeisel and Jacqueline Vischer
Bibliographic record
Abstract
Boxes #21-24 -- Books Dr. Jacqueline Vischer is an Environmental Psychologist specializing in environments for work. She is a founder of the field known as workspace psychology. She has published several books, including Environmental Quality In Offices (1989), Workspace Strategies: Environment As A Tool For Work (1996), L’Évaluation des environnements de travail : la méthode diagnostique (co-author Gustave-Nicolas Fischer, 1998), and Space Meets Status: Designing Workplace Performance (2005). In addition, Vischer has co-edited two books with Wolfgang Preiser. She speaks at trade shows and conferences throughout North America and in Europe, Asia and Australia, and she has contributed numerous chapters to volumes on facilities management, building performance, workplace psychology and building programming and evaluation. As expert consultant, Vischer has advised a wide range of organizations internationally on managing workspace comfort, designing innovative workspace, and planning workspace change. She is Professor Emeritus at the University of Montreal, where she successfully ran the Interior Design program and founded the New Work Environments Research Group (Groupe de recherche sur les environnements de travail). Many of her writings are available at – and can be downloaded from – www.jacquelinevischerbiu.com
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.449 | 0.309 |
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".