Change agency in a primary health care context
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Integration of services across disciplines and organizations has been pursued increasingly in the primary care sector. Successful integration requires adept leadership of change. There have been questions about the extent to which studies on change agency that focus on a stand-alone leader are applicable in the complex setting of health care. It has been suggested that a model of collective leadership is more appropriate to this setting. PURPOSE: The objective is to understand the dynamics of collective or distributed leadership by attending to change agency roles in a context involving collaboration across health organizations. The study examines how change agency roles develop, evolve, interact, and complement each other. It also examines the bases of the change agents' ability to exercise influence. METHODOLOGY: A qualitative, longitudinal case study allowed us to map the evolution of a successful model of leadership. We tracked changes and agents' roles by engaging in extensive observations and conducting 74 interviews over a period of 4 years. FINDINGS: The findings point to the importance of the distributed change leadership model in contexts where legitimacy, authority, resources, and ability to influence complex change are dispersed across loci. Distributed leadership has both planned and emergent components, and its success in bringing about change is associated with the social capital prevalent in the site. PRACTICE IMPLICATIONS: Change leaders need to build a winning coalition of agents with complementary skills and resources that support the change. Successful change leadership involves investing time in finding common ground across stakeholders and in building credibility and trust. Having an agent whose main responsibility is to manage the change process is likely to bring more success than asking busy health care practitioners to take on this charge because in the latter case, there is likelihood of dilution of change focus and momentum.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it