Supporting slow scholarship through building reading practices with first-year early childhood studies students
Bibliographic record
Abstract
This article details a two-year small pilot project investigating possibilities for enacting slow scholarship reading practices with first-year undergraduate early childhood studies students. We follow the emerging push to think with “slow” practices as an antidote to the consumptive, reproductive, fast-paced knowledge politics of the neoliberal university. To begin, we review the literature on slow scholarship in the early childhood studies and education context, before sharing the structure and content of the course that housed this slow-reading experiment. Then, we analyse student responses to an optional online questionnaire that gathered insights into their reflective experience of slow reading. We argue that slow reading disrupts quotidian student subjectivities and opens space for reconfiguring our relations with knowledge, which stretches beyond the post-secondary context into work with young children and families. To conclude, we offer provocations for cultivating slow-reading practices.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.001 | 0.004 |
| 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".