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Record W2012822700 · doi:10.2182/cjot.06.09

From Education to Occupation: The Story of Thomas Bessell Kidner

2007· article· en· W2012822700 on OpenAlexafffundvenueabout
Judith Friedland, Naomi Davids-Brumer

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2007
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsSt Joseph's Health CentreUniversity of Toronto
FundersUniversity of BristolAssociated Medical Services
KeywordsSociologyPsychologyGender studiesPedagogy

Abstract

fetched live from OpenAlex

BACKGROUND: Thomas Bessell Kidner is well-known in the United States as a great contributor to occupational therapy. He is not well-known in Canada despite the fact that his first contributions to the profession were made here between 1900 and 1918. PURPOSE: To tell the story of Thomas Bessell Kidner and his impact on occupational therapy. METHODS: Interpretive biography research methods using archival materials, published papers and family papers. RESULTS: Kidner's work as an organizer of manual training in elementary schools in Nova Scotia and New Brunswick and as Director of Technical Education for Calgary prepared him for his work as Vocational Secretary of the Military Hospitals Commission during World War I. Kidner developed, implemented and oversaw the reeducation program for injured soldiers across Canada. It included bedside occupations, off-ward and curative workshop activities provided by ward aides, as well as industrial training and apprenticeships in the workplace. PRACTICE IMPLICATIONS: Kidner's story stimulates us to revisit our profession's early emphasis on return-to-work. Knowing about our past helps occupational therapists to build a stronger identity.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.072
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.009
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.251
GPT teacher head0.526
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2007
Admission routes4
Has abstractyes

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