Old Enough to Know Better, dir. Ron Levaco, 2000. Available from First Run / Icarus Films, 32 Court Street, 21st Floor, Brooklyn, NY 11201. Videotape.
Bibliographic record
Abstract
RÉSUMÉ L'institut Fromm, situé à l'université de San Francisco, est un programme d'éducation des aîné(e)s remarquable comme le montre clairement la cassette vidéo Old Enough to Know Better. Lancé en 1976 à titre d'expérience d'une durée d'un an, ce programme, dont on célèbre aujourd'hui le cinquantième anniversaire, représente une union idéale entre un corps professoral en retraite et des personnes âgées qui désirent continuer à apprendre simplement pour le plaisir. La vidéo est un hommage au succès du programme comme l'illustre la série d'entrevues et de scènes prises dans la salle de classe. Cette étude se penche sur le modèle du programme, la pédagogie, les besoins des apprenants et des enseignants, ainsi que sur les bienfaits de l'éducation. Le but n'est pas, toutefois, de critiquer ce programme exceptionnel, mais de l'utiliser comme point de départ pour amorcer une réflexion critique sur le rôle vital que joue l'éducation dans la promotion d'une société qui vieillit sainement.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.485 | 0.329 |
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".