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Record W7097600391

TITLE Literacy and Health Project. Phase One. Making the World Healthier and Safer for People Who Can't Read.

2016· article· en· W7097600391 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsFunctional illiteracySAFERHealth literacySocioeconomic statusMultidisciplinary approachLiteracyVariety (cybernetics)Public health
DOInot available

Abstract

fetched live from OpenAlex

A research study examined the relationship between illiteracy and health. The study used the following methods for gathering information: review of health status data from major Canadian health status surveys: multidisciplinary literature review acrvss areas including medicine, health education, development, literacy, education, poverty, and socioeconomic status; questionnaire sent to Paolth and literacy organizations across Ontario; three case studiee at different sites in Ontario; and key informant interviews. The ma.jor finding was that illiteracy had a major, negative impact on health. This finding was consistent across a wide variety of measures of health status, including overall levels of mortality and morbidity, self-rated health, activity limitation, infant development, accidents, and a wide range of diseases. Evidence suggested that illiteracy leads to poorer health through a

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.772
Threshold uncertainty score0.460

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0030.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0290.008

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 head0.279
GPT teacher head0.574
Teacher spread0.295 · 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 designObservational
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

Citations0
Published2016
Admission routes1
Has abstractyes

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