Thomas Bessell Kidner, la trayectoria de un educador que marcó el rumbo de una nueva profesión, la terapia ocupacional
Bibliographic record
Abstract
espanolThomas Bessell Kidner (1866-1932), considerado uno de los fundadores de la Terapia Ocupacional, quien tuvo una gran influencia en Canada y EE.UU., vinculo la profesion con la medicina y fomento la formacion continua y la investigacion, unos valores que siguen muy presentes hoy dia. Estudio arquitectura y trabajo como educador y reformador de la educacion hasta que, desde el estallido de la Primera Guerra Mundial, se dedico a la rehabilitacion vocacional para el retorno al trabajo de los soldados heridos. Defendio el uso de las ocupaciones para tratar lesiones y enfermedades como la tuberculosis. Fue presidente de la AOTA durante varios anos, en los que promovio y construyo una infraestructura para la Terapia Ocupacional. EnglishThomas Bessell Kidner (1866-1932), is considered one of the founders of Occupational Therapy, had a great influence in Canada and United States, linked this profession to medicine and encouraged continuing training and research, values that remain strong today. He studied architecture and worked as an educator and educational reformer until, after the outbreak of the First World War, was devoted to vocational rehabilitation to the return to work of injured soldiers. He defended the use of occupations to treat injuries and diseases such as tuberculosis. He was the president of the AOTA for several years, on which he promoted and built an infrastructure for Occupational Therapy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".