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Record W3196135361 · doi:10.3138/cbmh.515-022021

Publishing and Paternalism in the Grenfell Mission: Wilfred Grenfell’s Accounts of a Boy Patient and Doctor-Patient Relations in Northern Newfoundland and Labrador, 1900–14

2021· article· en· W3196135361 on OpenAlexaffvenueabout
John R.H. Matchim

Bibliographic record

VenueCanadian Journal of Health History · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsAppealDramaLawHistoryMedicineArtPolitical scienceLiterature

Abstract

fetched live from OpenAlex

about a nine-year-old boy named Clem Richards, who had shot himself in the knee while hunting seabirds. The boy's identity was disclosed in full, with Grenfell including his name and image as well as a detailed description of his living conditions. The "story" of the boy's injury and recovery became a favourite of Grenfell's, and it was modified and republished in a number of magazines and books between 1906 and 1923. This article explores the appeal that Richards' accident held for Grenfell and argues that his dramatic mid-winter rescue of the boy helped Grenfell promote his mission and construct a public image of himself that would appeal to American readers and donors. By comparing published accounts with Richards' medical case record, however, we also see how much Grenfell distorted the incident to heighten its drama and reader appeal. The article also considers how the mission's dominance over northern Newfoundland and southeastern Labrador enabled Grenfell to use Richards' name and image for mission publicity with no consideration of patient consent.

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)0.004
metaresearch head score (Gemma)0.010
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.692

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0400.029
Scholarly communication0.0070.003
Open science0.0020.004
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0050.001

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 head0.025
GPT teacher head0.239
Teacher spread0.214 · 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

Citations2
Published2021
Admission routes3
Has abstractyes

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