“How Do You Measure a Relationship?” Assessment and Evaluation Challenges of Knowledge Exchange Activities in Information Work
Bibliographic record
Abstract
ABSTRACT Today there is increasing emphasis on knowledge exchange (KE), the movement of knowledge and expertise amongst diverse groups to enhance research uptake, use, and impact in healthcare, government, and community settings. Library and information science (LIS) professionals are central actors in KE though community engagement, scholarly communication, literacy, and cultural heritage initiatives, but (how) is this work formally documented and evaluated? Through interviews with 24 information professionals working in varied settings, we considered how KE activities fit into the current library assessment and evaluation landscape. Using thematic analysis, we identified challenges with placing this work within current assessment practices and evaluation frameworks and showing its value, as well as a desire for alternative, more dynamic assessment and evaluation methods. We discuss these findings with respect to previous research in LIS and KE more broadly to consider professional and organizational implications.
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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 | 0.332 | 0.496 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".