Bibliographic record
Abstract
The biography of Leonard and Reva Brooks is an adventure story in its own right.I cannot quickly think of any element it does not contain.Rags to riches, yes, it's there.Deportations, shootouts, spy and CIA factors, all there.Murders, murder attempts, suicide, the sexual picaresque, marital devotion, failures, triumphs, all duly accounted for.Not to mention an attendant array of personalities, non-personalities, life-clowns, and philosophers.Leonard and Reva Brooks each came of poor, not to say impoverished, backgrounds.And each received scant education.They ended up hobnobbing with the nabobs, ambassadors, and other artists as distinguished as themselves.The Canadian art scene beat a path to their door in San Miguel de Allende, Mexico.Dear friends as varied as Marshall McLuhan, Earle Birney, and the York Wilsons were frequently there.Not only Canadians, but as well the Mexican art elite recognized them and sought them out.Siqueiros was a great admirer, as was Gunther Gerzso.And Mexico, including the Mexican State, recognized their worth long before their home city of Toronto took real notice of them.In many ways it can be said that Toronto's neglect of the Brooks made them!They fled the frequent meanness of spirit in Toronto and settled in San Miguel de Allende soon after the Second World War, Leonard living off a small veterans' grant and his wits.Teaching at Bellas Artes, the fine arts school, in San Miguel.No, they didn't intend to settle there.But force of circumstances, lack of art jobs in Canada and the pervasive hostility of the Canadian art scene, kept them there.To their benefit, and finally to posterity's benefit.All that is to oversimplify.There is an entire Brooks story and trajectory prior to their Mexico years.Leonard's time in England, in Spain, travelling threadbare.Sometimes helped by artists as distinguished as Sir Frank Brangwyn.A picaresque time, yes, and picturesque, very.But the core story is the years in San Miguel de Allende, from 1947 to the present.Story culminating in San Miguel as Leonardbrooksland.Or as famous cellist Gilberto Munguia put it recently: "I consider Leonard to be the inspiration, the impulse, the catalyst, that set off the marvellous migration of northerners to San Miguel.Not only did he inspire the art scene but also the music scene ..."
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.773 | 0.750 |
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".