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Record W2129692163 · doi:10.1177/1049732313508843

Sanitoriums and the Canadian Colonial Legacy

2013· article· en· W2129692163 on OpenAlexaffabout
Jessica Moffatt, Maria Mayan, Richard Long

Bibliographic record

VenueQualitative Health Research · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of AlbertaInstitute of Health Economics
FundersPublic Health Agency
KeywordsSnowball samplingNonprobability samplingQualitative researchTuberculosisContent analysisData collectionSample (material)Perspective (graphical)SociologyMedicinePsychologySocial scienceDemographyPathology

Abstract

fetched live from OpenAlex

Sanitoriums served a much-needed purpose in the age prior to antituberculosis drugs: They removed the infected patient from wider society and created an environment that promoted recovery. We aimed to (a) describe sanitoriums from the perspective of a First Nations reserve community in northern Canada and (b) understand the impact of the sanitorium experience at a community level. Semistructured interviews (n = 15) were conducted in a First Nations reserve community with a high incidence of tuberculosis. Purposive and snowball sampling were used to obtain the sample. Data collection and analysis were iterative, using qualitative content analysis. Participants described the exclusion resulting within and because of sanitoriums. Exclusion within sanitoriums was categorized into (a) the exclusion of Aboriginal culture and practices of healing from the treatment of tuberculosis and (b) the internal exclusion, in which members of the community internally labeled the healed individual postsanitorium as an outsider.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.094
Threshold uncertainty score0.679

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0390.023
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.235
GPT teacher head0.560
Teacher spread0.325 · 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

Citations25
Published2013
Admission routes2
Has abstractyes

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