Examining partnerships within an international knowledge translation network focused on youth mental health promotion
Bibliographic record
Abstract
BACKGROUND: Systems transformation for health promotion, involving engagement from multiple disciplines and levels of influence, requires an investment in partnership development. Integrated youth service is a collaborative model that brings organisations together to provide holistic care for youth. Frayme is an international knowledge translation network designed to support the uptake and scaling of integrated youth service. Social network analysis (SNA) is the study of relationships among social units and is useful to better understand how partners collaborate within a network to achieve major objectives. The purpose of this paper is to apply SNA to the Frayme network in order to (1) examine the level and strength of partnerships, (2) identify the strategies being employed to promote the main objectives and (3) apply the findings to current research in youth mental health and system transformation. METHODS: The PARTNER tool includes a validated survey and analysis software designed to examine partner interconnections. This tool was used to perform the SNA and 51 of the 75 partners completed the survey (14 researchers, 2 advisory groups and 35 organisations). A network map was created and descriptive frequencies were calculated. RESULTS: The overall network scores for the Frayme network were 20.6% for density, 81.5% for centralisation and 71.7% for overall trust. The Frayme secretariat received a 3.84 out of a possible 4 for value. In addition, the youth and family advisories each received a value score of 4 and all Leadership Team organisations received a score of 2.97 or above. CONCLUSIONS: The Frayme secretariat links many partners who would otherwise be disconnected and acts as a significant conduit for novel information. Frayme may have the opportunity to enhance value perceptions among broader network members by profiling individual organisations and the potential leveraging opportunities that might exist through their work. These findings increase understanding with respect to the mechanisms of network development and will be helpful to inform partnership development in the future. In addition, they contribute to the literature with respect to knowledge translation practice as well as the scaling of collaborative interventions within youth mental health.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| grok | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
| opus | MetaresearchScholarly communication Domain: Reporting · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.027 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".