Library and Information Professionals as Knowledge Engagement Specialists. Theories, Competencies and Current Educational Possibilities in Accredited Graduate Programmes.
Bibliographic record
Abstract
Introduction. The role of library and information science professionals as knowledge facilitators is solidly grounded in the profession's theoretical foundations as much as connected with its social relevance. Knowledge science is presented in this paper as a convenient theoretical framework for this mission, and knowledge engagement services –knowledge brokering, knowledge readiness and knowledge promotion -a s an area that might serve to reframe and expand traditional services such as reference, information literacy and outreach and cultural programming. A key competency for knowledge engagement specialists is mastering instruction, aimed at the efficient fostering of innovation and the creation of new knowledge within organizations and society. The purpose of this paper is to analyse current supply of courses covering instructionalrelated competencies in accredited graduate programmes. Methods. Main professional competency standards and courses currently offered in accredited graduate programmes (United States, Canada, United Kingdom and Australia) are analysed. Results. Results suggest that although some relevant competencies have been included by professional associations in their competency standards for all types of information professionals, instructional competencies have not received much attention in graduate educational programmes other than in concentrations or tracks targeted at future school or academic librarians. Conclusion. It is concluded that further research on competencies and education for knowledge engagement is required in order to fully develop this role within the profession.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".