Intersectionality: A Framework for Children with Special HealthCare Needs Research
Bibliographic record
Abstract
Introduction: The experience of children with special healthcare needs (CSHCN) who hold multiply marginalized identities is underrepresented in healthcare research literature. Even less research investigates the impact of multiple systems of oppression on CSHCN experiences with healthcare providers, services, and systems. Methods: To identify gaps and areas of future research, in early 2020, a scoping review of current CSHCN healthcare literature that includes an explicit intersectionality framework or analysis was conducted. Findings: Based on the literature search results, there were zero peer reviewed articles within the CSHCN research literature that included a framework or analysis of intersectionality. Implication: CSHCN have diverse lived experiences. An explicitly intersectional approach is best suited to creating programs, treatments, interventions, and service provision that address the truly complex needs of this population within the U.S. dominant culture. Promising frameworks and future research needs are discussed.
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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 | 0.094 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.027 | 0.015 |
| Science and technology studies | 0.018 | 0.099 |
| Scholarly communication | 0.025 | 0.040 |
| Open science | 0.007 | 0.031 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".