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Record W3042823649 · doi:10.4081/jphr.2020.1696

Colon Cancer Care of Hispanic People in California: Paradoxical Barrio Protections Seem Greatest among Vulnerable Populations

2020· article· en· W3042823649 on OpenAlexaff
Keren M. Escobar, Mollie Sivaram, Kevin M. Gorey, Isaac Luginaah, Sindu Kanjeekal, Frances C. Wright

Bibliographic record

VenueJournal of public health research · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of TorontoMcMaster UniversitySunnybrook Health Science CentreWindsor Regional HospitalWestern UniversityUniversity of Windsor
Fundersnot available
KeywordsPovertyCohortMedicineDemographyGerontologyCancerCohort studyPolitical scienceSociologyInternal medicine

Abstract

fetched live from OpenAlex

Background We examined paradoxical and barrio advantaging effects on cancer care among socioeconomically vulnerable Hispanic people in California. Methods We secondarily analyzed a colon cancer cohort of 3,877 non-Hispanic white (NHW) and 735 Hispanic people treated between 1995 and 2005. A third of the cohort was selected from high poverty neighborhoods. Hispanic enclaves and Mexican American (MA) barrios were neighborhoods where 40% or more of the residents were Hispanic or MA. Key analyses were restricted to high poverty neighborhoods. Results Hispanic people were more likely to receive chemotherapy (RR=1.18), especially men in Hispanic enclaves (RR=1.33) who were also advantaged on survival (RR=1.20). A survival advantage was also suggested among MA men who resided in barrios (RR=1.80). Conclusions The findings were supportive of Hispanic paradox and MA barrio advantage theories. They further suggested that such advantages are greater for men, perhaps due to their greater spousal and extended familial support.

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 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)0.004
metaresearch head score (Gemma)0.003
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 score0.086
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.609
GPT teacher head0.528
Teacher spread0.081 · 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 teacher head, 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

Citations7
Published2020
Admission routes1
Has abstractyes

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