Áhrif niðurskurðar á starfshvata og innbyrðis þekkingarmiðlun heilsugæsluhjúkrunarfræðinga
Bibliographic record
Abstract
The aim of the paper is twofold: Firstly, to examine the effects of cutbacks related to the the economic collapse on the motivating factors among nurses in primary health care and, secondly, to examine the effects of the cutbacks on the knowledge sharing within the same group. A qualitative method, the Vancouver-school of doing phenomenology, was used, involving a purposeful sample of ten nurses in primary health care. The results indicate that the cutbacks increased pressure, fatigue, lack of time and employment insecurity among the participants. Continuing education and professional development was negatively affected and job security and salaries became stronger motivating factors than before. Lack of time and a heavy workload hindered spontaneous knowledge sharing while organized knowledge sharing was less affected. From thisit can be learned that cutbacks can have serious effects on motivationalfactors among health care professionals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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 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".