Time, New Public Management, and Canadian Academic Librarians’ Scholarship and Service
Bibliographic record
Abstract
Time is a critical factor in the success of librarians’ scholarship. Shared perceptions of organizational time enable, regulate, and constrain performance. Under the values and practices of New Public Management (NPM), intended to increase accountability and efficiency in the public sector, time in the university has become accelerated, intensifed, fragmented, and commodifed. Feminist and anti-colonial scholars remind us of the differentiated temporal impacts of NPM on women and other minorities in higher education, yet to date, its impact on the feminized profession of librarianship has not been examined. Using data from semi-structured interviews with 24 librarians working in Canadian U15 public research-intensive universities, the present article seeks to address this gap by exploring the impact of neoliberal timescapes on librarians’ scholarship and professional-service activities. Findings indicate that time is an important mechanism through which neoliberal governmentality is enacted. Being a “successful” researcher is largely dependent on intrinsic motivation and self-regulation. Trying to work with, rather than against, neoliberal timescapes facilitates research. Results also suggest that conficting organizational timescapes may exist between library directors and librarians, and that, as researchers, Canadian academic librarians are being held accountable to ambiguous performance standards and impracticable timescapes.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.029 | 0.025 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
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".