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Record W2111055606 · doi:10.1177/0013916504269651

Individual and Neighborhood Characteristics Associated with Environmental Exposure

2005· article· en· W2111055606 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironment and Behavior · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsEnvironmental healthLogistic regressionPsychologyEnvironmental qualityBlue collarPopulationSocioeconomicsGeographyMedicineDemographic economicsSociologyStatisticsMathematicsEcology

Abstract

fetched live from OpenAlex

Environmental exposure research tends to emphasize the monitoring and regulation of emissions, with fewer investigations of exposure experienced in the general population. To help bridge the gap between environmental quality and perceived exposure, this study examines ambient exposures among 300 residents from each of 4 neighborhoods and among a control group of 300 residents in Hamilton, Ontario, Canada. Logistic regression analyses determined how individual, neighborhood, and housing characteristics influenced self-reported exposure in the workplace, inside the home, and around the home. Blue-collar occupations, neighborhood dislikes, and a home in disrepair were associated with work exposure. Neighborhood dislikes, renting, and indicating how the neighborhood could be healthier were associated with indoor exposure. Pesticide exposure was linked to professional occupations and to a specific neighborhood. Older homes were also associated with pesticide and indoor exposure. The findings highlight the need for further research on indoor exposure indices and on perceptions of neighborhood quality.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.787

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.244
Teacher spread0.228 · 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