Bibliographic record
Abstract
The Biography of an Enigma Born in Ireland in 1879, W.P.M. Kennedy was a distinguished Canadian academic and the leading Canadian constitutional law scholar for much of the twentieth century.Despite his trailblazing career, Kennedy has been a largely mysterious figure.Now, weaving together a number of key events and drawing on Kennedy's personal letters, Martin L. Friedland presents a lively biography of the man.Searching for W.P.M. Kennedy discusses Kennedy's contributions as a legal and interdisciplinary scholar and his work at the University of Toronto, where he founded the Faculty of Law.The book also details Kennedy's intriguing personal life, presenting stories about Kennedy's family and important friends, such as Prime Minister Mackenzie King.Kennedy earned a reputation in some circles for being something of a scoundrel, and Friedland does not shy away from addressing Kennedy's exaggerated involvement in drafting the Irish constitution, his relationships with female students, or his constant quest for recognition.Throughout the biography, Friedland interjects his own personal narratives surrounding his interactions with the Kennedy family, including how he came to acquire the private letters noted in the book.The result is a highly readable biography of an important figure in the history of Canadian intellectual life.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.733 | 0.580 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".