Self-care in New Zealand: The role of the community pharmacy
Bibliographic record
Abstract
Self-care is a growing area in community pharmacy globally. In a time where people are taking control over their own health care, the question of the degree of self-care available from community pharmacies is pertinent. New Zealand is a country that has publicly funded healthcare; with over 1000 community pharmacies catering to a population of 5 million people. Despite the availability and accessibility of community pharmacies, much remains unknown about how self-care is offered in community pharmacies and the extent to which it is provided. In addition to this lack of clarity, is the current period of reorganisation occurring in the New Zealand healthcare system. The current changes involve dis-establishing district health boards (DHBs) and unifying the New Zealand health system into one streamlined system. It leads us to question whether this move will change funding allocations and health priorities as well as how they affect service provision in community pharmacy. While research has shown that New Zealand is paving the way in medicines reclassification making medicines more accessible, other research shows a fragmentation exists in services provided by community pharmacies in the area of self-care. This article will highlight what is currently known about self-care in New Zealand, the gaps that exist and the current challenges in this area.
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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 | 0.011 |
| 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 | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".