MétaCan
Menu
Back to cohort
Record W2973171595 · doi:10.15453/0191-5096.4106

Multiplicative Advantages of Hispanic Men Living in Hispanic Enclaves: Intersectionality in Colon Cancer Care

2019· article· en· W2973171595 on OpenAlexafffund
Keren M. Escobar, Mollie Sivaram, Kevin M. Gorey

Bibliographic record

VenueThe Journal of Sociology & Social Welfare · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsMcMaster UniversityUniversity of Windsor
FundersNational Cancer InstituteCenters for Disease Control and PreventionCancer Registry of Greater CaliforniaCalifornia Department of Public HealthUniversity of WindsorUniversity of TorontoUniversity of Southern California
KeywordsIntersectionalityEthnic groupGerontologyMedicineImmigrationDemographyGender studiesGeographyPolitical scienceSociology

Abstract

fetched live from OpenAlex

We examined Hispanic enclave paradoxical effects on cancer care among socioeconomically vulnerable people in pre-Obamacare California. We conducted a secondary analysis of a historical cohort of 511 Hispanic and 1,753 non-Hispanic white people with colon cancer. Hispanic enclaves were neighborhoods where 40% or more of the residents were Hispanic, mostly first-generation Mexican American immigrants. An interaction of ethnicity, gender and Hispanic enclave status was observed such that the protective effects of living in a Hispanic enclave were larger for Hispanic men, particularly married Hispanic men, than women. Risks were also exposed among other study groups: the poor, the inadequately insured, Hispanic men not residing in Hispanic enclaves, Hispanic women and unmarried people. Implications for the contemporary health care policy debate are discussed.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.334
Teacher spread0.323 · 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 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

Citations3
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Sociology & Social WelfareSame topicMigration and Labor DynamicsFrench-language works237,207