Bibliographic record
Abstract
Purpose Library staff are experiencing increased work role complexity as they move from being service providers towards greater instructional roles, providing bibliographic instruction, user education, and information literacy instruction. The purpose of this paper is to explore how library staff relate to their instructional roles and the implications of those self‐understandings for instructional outcomes. Design/methodology/approach Data collected from qualitative interviews with library staff in Canadian academic and public libraries and diary entries written over a three‐month period were analyzed using NVivo software and an open‐coding, grounded‐theory approach. The study took a phenomenological perspective and was influenced by constructivist sociological role theory. Findings Data analysis revealed the central place of affect in the experiences of librarians engaged in instructional work, and brought focus to the relational aspects of this work and the affective impact of visibility/invisibility of instructional outcomes. A prominent theme was the expression of “emotional labour”; participants used a variety of methods to manage this occupational stressor as they experienced it within the context of instructional work. Practical implications Individuals and organizations will benefit from considering the influence of affect on library staff. Those who educate librarians should seek to improve understanding of affect and its impact on instruction; organizations will benefit from addressing the emotional labour performed as a part of the teaching role. Originality/value The study draws attention to the affective experiences of library staff. This is the first research article in the LIS literature to explore emotional labour as it relates to librarians.
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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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; 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".