Fostering international collaboration in implementation science and research: a concept mapping exploratory study
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
OBJECTIVE: International collaboration in science has received increasing attention given emphases on relevance, generalizability, and impact of research. Implementation science (IS) is a growing discipline that aims to translate clinical research findings into health services. Research is needed to identify efficient and effective ways to foster international collaboration in IS. Concept-mapping (CM) was utilized with a targeted sample for preliminary exploration of fostering international collaboration. Concept-mapping is a mixed-method approach (qualitative/quantitative) particularly suited for identifying essential themes and action items to facilitate planning among diverse stakeholders. We sought to identify key factors likely to facilitate productive and rewarding international collaborations in implementation research. RESULTS: We identified eleven dimensions: Strategic Planning; Practicality; Define Common Principles; Technological Tools for Collaboration; Funding; Disseminate Importance of Fostering International Collaboration in IS; Knowledge Sharing; Innovative & Adaptive Research; Training IS Researchers; Networking & Shared Identity; Facilitate Meetings. Strategic Planning and Funding were highest rated for importance and Strategic Planning and Networking and Shared Identity were rated most feasible to institute. Fostering international collaboration in IS can accelerate the efficiency, relevance, and generalizability of implementation research. Strategies should be developed and tested to improve international collaborations and engage junior and experienced investigators in collaborations advancing implementation science and practice.
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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 | 0.051 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it