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Record W2022511592 · doi:10.3402/ijch.v64i1.17949

Otitis media: health and social consequences for aboriginal youth in Canada’s north

2005· review· en· W2022511592 on OpenAlexaffabout
Alan D. Bowd

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2005
Typereview
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsLakehead University
Fundersnot available
KeywordsOtitisSocial mediaPsychologyMedicinePolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: Otitis media is endemic among Inuit, First Nations and Métis children in northern Canada, with prevalence rates in some communities as high as 40 times that found in the urban south. Hearing impairment, much of it attributable to chronic otitis media, is the most common health problem in parts of the arctic, and conductive hearing loss among children may affect as many as two-thirds. STUDY DESIGN AND METHODS: There is a need for systematic data based on consistent disease definitions and measures, and taking account of cross-cultural methodological issues and sampling. RESULTS: Otitis media is most likely to develop in infancy. Susceptibility has been linked to immune defects and to a variety of environmental factors. Among the most significant are diet, the decline in initiation and maintenance of breastfeeding, and exposure to cigarette smoke. Hearing loss has been related to difficulties in language acquisition, and to subsequent issues with literacy and school achievement, including learning disabilities and attention deficits. The economic and social costs of otitis media are substantial. CONCLUSION: Approaches to treatment and prevention have enjoyed limited success. Public health and medical practice need to be informed by the traditional knowledge and practices of indigenous peoples.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.358
Threshold uncertainty score0.721

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.073
GPT teacher head0.399
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 designNot applicable
Domainnot available
GenreReview

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

Citations58
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Circumpolar HealthSame topicEar Surgery and Otitis MediaFrench-language works237,207