MétaCan
Menu
Back to cohort
Record W2001907778 · doi:10.1177/1084822304268156

Improving Cancer Awareness among Asian Americans Using Targeted and Culturally Appropriate Media: A Case Study

2004· article· en· W2001907778 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.

Bibliographic record

VenueHome Health Care Management & Practice · 2004
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsAtlantic Cancer Research Institute
Fundersnot available
KeywordsVietnameseCancer preventionMedicineCancerCervical cancerMainstreamChinese americansCancer screeningBreast cancer awarenessBreast cancerFamily medicineEthnic groupPolitical science

Abstract

fetched live from OpenAlex

Reaching Asian Americans with cancer awareness messages is critical to improving cancer detection and reducing risk. Two separate targeted media campaigns, sponsored by the Asian Tobacco Education, Cancer Awareness, and Research (ATECAR), were implemented to increase cancer awareness among Chinese, Koreans, Vietnamese, and Cambodians residing in Philadelphia and the surrounding counties. These campaigns, based on Rogers’s diffusion and innovation theoretical model, were culturally sensitive, multilingual, and implemented over an extended time frame using print articles and a radio series under the respective general headings ATECAR Link and Voice of ATECAR. The series covered a range of topics that included tobacco smoking and health, cervical and breast cancer, clinical trials, and cancer information. Despite a reputation for noninvolvement in mainstream cancerrelated media issues, results of the campaigns reflected an exceptional response from the targeted communities. The results suggest that wellplanned, community-based media campaigns can have positive impacts on cancer awareness in Asian communities.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.186
GPT teacher head0.541
Teacher spread0.355 · 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