Isolated, individualised, and immobilised: information behaviour in the context of academic casualisation
Bibliographic record
Abstract
Introduction. Universities rely increasingly on contract academic staff for teaching and research activities; yet, working in precarious conditions, these staff face significant challenges in finding relevant workplace information, in engaging with colleagues, and in building their careers. This study examines contract academic staff perceptions of precarity and workplace marginalisation, focusing on the implications of situational and environmental influences on their information practices. Method. In-depth, semi-structured interviews with 34 contract academic staff, working in various disciplines across Canadian universities, were conducted to examine their information practices. Analysis. Interview data were analysed using reflexive thematic analysis, drawing on everyday life information seeking and information marginalisation theories. Results. Results of the study show that 1) contract academic staff conduct their work within isolated information environments; 2) this isolation leads these staff to develop highly individualised information practices; and 3) the information activities of contract academic staff are often immobilised, due to the precarious contexts that shape their work and personal lives. Conclusion. Precarious employment and information marginalisation are deeply entwined for contract academic staff. This results in frustration, disappointment, and uncertainty with their work and personal circumstances. Institutional challenges can seem intractable, particularly where task-related information provision (when available) cannot address systemic concerns.
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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 | 0.009 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".