Studying Delays in Breast Cancer Diagnosis and Treatment: Critical Realism as a New Foundation for Inquiry
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To examine how delays in breast cancer care currently are conceptualized and to introduce philosophical and theoretical tenets of critical realism as an alternative approach. DATA SOURCES: Health and social sciences literature. DATA SYNTHESIS: Diagnostic and treatment delays in breast cancer most frequently are conceptualized as patient, provider, or system related. The approach has limited utility in guiding explanatory analysis because it does not acknowledge the social context in which the delays occur. The philosophical tenets of critical realism and two related theoretical approaches are an alternative. They illustrate how an individual's biologic, social, and material resources may undermine or support structural inequities in access to breast cancer care. CONCLUSIONS: Critical realism provides a useful framework for analysis of links between social inequalities and delays in breast cancer diagnosis and treatment. IMPLICATIONS FOR NURSING: Access to breast cancer care could be better understood and conceptualized by basing future research and theoretical endeavors on a critical realist perspective.
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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 | 0.046 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.063 |
| Scholarly communication | 0.010 | 0.024 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".