Person Centered Care: Which Person? What Care? Equity Dilemmas through a marginalized Patient Lens
Bibliographic record
Abstract
Patient centered care is an important pillar of innovative integrated approaches for quality improvement of healthcare systems and capacity building context for all healthcare stakeholders. Yet critical questions remain unexplored in the approach, relating to (a) assumptions about largely homogeneous nature of patients and (b) evaluation of the relevance of care within the patient unique social contexts. In reality, patients -globally - are neither a homogeneous community or a monolithic entity. The inadequate recognition of diversities of contexts, particularly in sub groups of vulnerable patient population within the fast changing social determinants of their wellbeing, remain a serious challenge for innovations; it often limits their intent for transforming the system into disparate initiatives for reforms, addressing traditional features of healthcare delivery within the customary standards of historical silos that characterized the system in the past. The proposed networking session focused on the pillars of Shared Values and Peron centered Care, aims to facilitate a meaningful dialogue related to complex dilemmas of Innovations in Integrated Care. It focuses on exploring sustainable goals of patient partnership to enhance innovations that acknowledge the need for embedding diversity, inclusion, equity and access in design, delivery and evaluation within approaches of integrated healthcare. * Esha Ray Chaudhuri is a Patient Advocate and Health Equity Analyst in Calgary, Canada
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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 | 0.035 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.079 |
| Scholarly communication | 0.025 | 0.027 |
| Open science | 0.003 | 0.025 |
| Research integrity | 0.013 | 0.029 |
| Insufficient payload (model declined to judge) | 0.006 | 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".