Integrating Social Work Perspectives into LIS Education: Blended Professionals as Change Agents
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
Abstract Purpose – In this chapter, I present a systematic discussion of the relationship between social work (SW) and library and information science (LIS) and explore how SW can contribute to the education of LIS practitioners so that they become more than information facilitators and grow professionally to be true agents of change. Design/Methodology/Approach – Using engagement with immigrant communities as a case in point and building on the empirical comparative study of public librarians in the Greater Toronto Area and New York City, I outline the current gaps and deficiencies of LIS curricula that can be rectified through blended education. I also integrate the potential contributions of SW into LIS through the case study of an immigrant member of a library community. Findings – Building on the case study, I introduce a four-tiered model that can be applied to a wide array of courses in LIS programs and conclude with suggestions for taking steps toward blending SW perspectives into the LIS curriculum. Originality/Value – I position the potential fusion of SW and LIS as “professional blendedness,” which serves as a catalyst for change, and also examine the concept of the blended professional as a change agent. I introduce the rationale for adopting theoretical, practical, and pedagogical approaches from SW in the field of LIS and focus on four specific contributions that can most benefit LIS:
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.032 | 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 it