Bibliographic record
Abstract
What Led Me to Philosophy and Philosophy of EducationI grew up on a somewhat remote sheep farm in Western Australia and did my early and final years of schooling by distance education.My mother was a school teacher so she could help supervise me, especially in grades 1 and 2. From grades 3 to 10, I went by bus to local public schools.The last two "leaving" years were spent in splendid isolation doing correspondence courses.My two older brothers led the flight from farm to university and, when I finished school, I went off to the University of Western Australia (UWA).My four-year B.Ed. degree included teacher certification.However, I also opted for some fairly academic studies: honours in philosophy of education, a major in history, and courses in philosophy and Greek.After graduating, I worked part-time and enrolled in another bachelor's degree at the University of Sydney, doing honours in general philosophy and more courses in classical Greek.I then became a lecturer in philosophy of education at the University of New England (UNE), just north west of Sydney.At the same time, I did a Ph.D. in philosophy at UNE with a focus on philosophy of education.In 1967, I got a position in philosophy of education at the Ontario Institute for Studies in Education (OISE) at the University of Toronto on the recommendation of Israel Scheffler, one of my doctoral examiners.Given my roots, why all this early interest in philosophy and philosophy of education?Cynics might explain it in terms of exposure to vast horizons and myriad sheep.Others might refer to my strongly religious upbringing (long since left behind).But the farm experience was, of course, quite practical, and our religion was rather unreflective, concerned more with getting into the next world than understanding the present one.I think it was more a matter of personality.It was in my nature to enjoy theorizing about life, society, and reality in general.Also, being something of an optimist, I had accepted (naively, I think now) the general Western notion that "the truth will make you free", that getting to the bottom of things leads rather quickly to personal and societal transformation.I saw philosophy not only as enjoyable but as potentially very useful.Finally, philosophy of education at that time offered employment, and with wool prices plummeting, it seemed like a congenial alternative. Early Experiences in Philosophy and Philosophy of EducationAt UWA, my sole instructor and honours supervisor in philosophy of education was T.A. (Bert) Priest.He broadly advocated the British analytic approach to philosophy and introduced us to thinkers such as A.J.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.025 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".