Bibliographic record
Abstract
Pask to the FutureIn 1979, I helped welcome the British cyberneticist, Gordon Pask, to Montréal.He stood out from the crowd, sporting a powder blue riding jacket, derby, and the mandatory English brolly.Over lunch, he animatedly expounded on his ideas of educational cybernetics, knocking the wine onto the table and his p-soup into his lap.After clearing the collateral damage, we carried on to the Concordia University TV studio to record his presentation on conversation theory.Whether due to the audience, the lights, or the lunch, the talk quickly disintegrated into a disjointed ramble and was never edited into a final program.Gordon stayed in Montréal for a few years, building prototypes of conversationally linked documents and sharing his philosophy of serialist versus holist learning styles in well-lubricated graduate seminars.Unfortunately, his ability to express his ideas was severely limited by the technology of the day, his confusing notational system, and the spirits of Montréal.So few comprehensive works emerged that Nigel Ford's book might well be valued as the best beginners' guide to Pask's ideas.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.093 | 0.032 |
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".