Bibliographic record
Abstract
Breast cancer incidence and mortality rates are of concern among Latin American women, mainly due to the growing prevalence of this disease and the lack of compliance to proper breast cancer screening and treatment. Focusing on Venezuelan women and the challenges and barriers that interact with their health communication, this paper looks into issues surrounding women's breast cancer, such as the challenges and barriers to breast cancer care, the relevant ethics and responsibilities, the right to health, breast cancer risk perception and risk communication, and the media interventions that affect Venezuelan women's perceptions and actions pertaining to this disease. In particular, it describes an action-oriented research project in Venezuela that was conducted over a four-year period of collaborative work among researchers, practitioners, NGOs, patients, journalists, and policymakers. The outcomes include positive indications on more effective interactions between physicians and patients, increasing satisfactions about issues of ethical treatment in providing healthcare services, more sufficient and responsible media coverage of breast cancer healthcare services and information, a widely supported declaration for a national response against breast cancer in Venezuela, and the creation of a code of ethics for the Venezuelan NGO that led the expansion of networking in support of women's breast cancer healthcare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".