The performance of primary health care organizations depends on interdependences with the local environment
Bibliographic record
Abstract
Purpose Improving the performance of health care organizations is now perceived as essential in order to better address the needs of the populations and respect their ability to pay for the services. There is no consensus on what is performance. It is increasingly considered as the optimal execution of four functions that every organization must achieve in order to survive and develop: reach goals; adapt to its environment; produce goods or services and maintain values; and a satisfying organizational climate. There is also no consensus on strategies to improve this performance. The paper aims to discuss these issues. Design/methodology/approach This paper intends to analyze the performance of primary health care organizations from the perspective of Kauffman's model. It mainly aims to understand the often contradictory, paradoxical and unexpected results that emerge from studies on this topic. Findings To do so, the first section briefly presents Kauffman's model and lays forward its principal components. The second section presents three studies on the performance of primary organizations and brings out the contradictory, paradoxical and unexpected results they obtained. The third section explains these results in the light of Kauffman's model. Originality/value Kauffman's model helps give meaning to the results of researches on performance of primary health care organizations that were qualified as paradoxical or unexpected. The performance of primary health care organizations then cannot be understood by only taking into account the characteristics of these organizations. The complexity of the environments in which they operate must simultaneously be taken into account. This paper brings original development of an integrated view of the performance of organizations, their own characteristics and those of the local environment in which they operated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".