The influence of partnership centrality on organizational perceptions of support: a case study of the AHLN structure
Bibliographic record
Abstract
BACKGROUND: Knowledge of the structure and character of inter-organizational relationships found among health promotion organizations is a prerequisite for the development of evidence-based network-level intervention activities. The Alberta Healthy Living Network (AHLN) mapped the inter-organizational structure of its members to examine the effects of the network environment on organizational-level perceptions. This exploratory analysis examines whether network structure, specifically partnership ties among AHLN members, influences organizational perceptions of support after controlling for organizational-level attributes. METHODS: Organizational surveys were conducted with representatives from AHLN organizations as of February 2004 (n = 54). Organizational attribute and inter-organizational data on various network dimensions were collected. Organizations were classified into traditional and non-traditional categories. We examined the partnership network dimension. In- and out-degree centrality scores on partnership ties were calculated for each organization and tested against organizational perceptions of available financial support. RESULTS: Non-traditional organizations are more likely to view financial support as more readily available for their HEALTR programs and activities than traditional organizations (1.57, 95% CI: .34, 2.79). After controlling for organizational characteristics, organizations that have been frequently identified by other organizations as valuable partners in the AHLN network were found significantly more likely to perceive a higher sense of funding availability (In-degree partnership value) (.03, 95% CI: .01, .05). CONCLUSION: Organizational perceptions of a supportive environment are framed not only by organizational characteristics but also by an organization's position in an inter-organizational network. Network contexts can influence the way that organizations perceive their environment and potentially the actions that organizations may take in light of such perceptions. By developing evidence-based understandings on the influence of network contexts, the AHLN can better target the particularities of its specific health promotion network.
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 | 0.004 | 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 | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".