P041 Sustaining organizational capacities of knowledge utilization: A complete toolbox for the health and social services organizations
Bibliographic record
Abstract
Background Despite research and funding, the understanding of organization’s capacities of knowledge utilisation remains incomplete in health and social field. Objectives To better understand organisational determinants of research result utilisation. Method Between 2009 and 2012, managers (n = 75) from health and social services organisations (N = 8) have actively contributed in a participative research action process. Additionally professionals and managers (N = 2161) have answered questionnaires. Qualitative and quantitative data gathered on the organisational outcomes as well as on the process of using our tool provided empirical validation. This iterative process led to the creation of a complete toolbox designed to help organisations raise to the knowledge transfer and utilisation challenge. Results The toolbox includes a conceptual framework, a user’s guide and two questionnaires to establish a diagnostic of the organisation’s capacities of knowledge utilisation and to identify the main strategies to improve them. At the root of our toolbox is a theoretical model of organisational capacities to use knowledge, specific to health and social services organisations, that we have developed. Our model includes eight components: organisational culture, vision and leadership, knowledge acquisition, reflexivity, integration, creation and dissemination, adaptation, and relationships. Discussion The results demonstrate that the toolbox helps decision makers to develop a common understanding of their organisation’s strengths and weaknesses in terms of research knowledge utilisation capacities. Implications:The research and toolbox developed by our team provide a first step in unveiling the intricacies of knowledge utilisation in the social services sector. Eight key organisational capacities were found to be essential in facilitating and promoting knowledge utilisation in health and social services.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.017 | 0.021 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".