Navigating barriers and pathways in capacity development for knowledge mobilization: perspectives from McGill University’s Faculty of Education
Bibliographic record
Abstract
Introduction This study offers a case study of capacity development for Knowledge Mobilization (KMb) within the context of McGill University’s Faculty of Education, focusing on the experiences of researchers and students engaged in KMb. Amidst increasing global demands for academic research to contribute to societal benefits, this case study evaluated the participants’ experiences of challenges and support received in doing KMb activities. Methods This case study followed a qualitative exploratory approach, utilizing semi-structured interviews to gather detailed insights from graduate students and faculty members within McGill University’s Department of Integrated Studies in Education (Montreal, Canada). Ten participants were selected through convenience sampling, to provide a diverse representation of experiences in engaging with KMb practices. The study’s inductive data analysis strategy allowed for a comprehensive analysis of the challenges and supports related to KMb and grounded findings in the real-world experiences and perspectives of those directly involved in KMb efforts. Results The research revealed organizational challenges, including inadequate recognition of KMb efforts and insufficient institutional support, as significant barriers to effective KMb. Despite these obstacles, certain enablers, such as KMb training and supportive relationships with supervisors, highlight the potential pathways for enhancing KMb capacity. Notably, the study uncovered a discrepancy between the availability and accessibility of KMb support, pointing to the necessity of tailored, accessible capacity development strategies. Discussion By emphasizing the need for systemic changes and prioritizing organizational capacity development, this research contributes to a more nuanced understanding of fostering effective and inclusive KMb practices with faculties of Education and beyond.
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 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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.039 | 0.021 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".