Components of Equity-Oriented Health Care System: Perspective of Iranian Nurses
Bibliographic record
Abstract
Equity in health is one of key objectives in health care systems world wide. This study aimed to explain the perspective of Iranian nurses about equity in the health care system. A qualitative exploratory design with thematic analysis approach was used to collect and analyze data. Using a purposeful sampling helped the researchers to recruit 16 eligible participants. Data were collected via in-depth semi-structured interviews. Five main categories were extracted through data analysis process including (1) inequity against the nurse, (2) the recommended patient, (3) no claim for equity-oriented care in health system, (4) physicians' dominancy system; and (5) the need to define criteria to measure equity-oriented care. All health care systems around the world struggle to establish equity-oriented care. In perspective of Iranian nurses, the reform of structures in the health system is possible through providing the context of equitable care for caregivers and care recipients. Health system should commit the flow of equity at all of its levels. It should utilize policies to claim equity and consider the interests of all beneficiaries. Furthermore, certain criteria should be defined for equity-oriented care in the health care system, and also provides the possibility to measure and monitor it.
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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 | 0.005 | 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 | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".