Bibliographic record
Abstract
This talk operates on the assumption that critique is important, but acts of imagination and possibility are necessary now more than ever, both in the academy and society more broadly. Inspired by Frederic Jameson reimagining utopia, I am responding to Gaudry and Lorenz's call to envision a socially just Canadian academy beyond mechanisms of inclusion (2018). Recognizing contemporary debates of indigenization of academic spaces and programs in Canada, I am interested in adopting the ideas of a resurgence-based decolonial indigenization as an opportunity to apply the benefits of balanced power relations to all learners. From this starting point, I explore the digital scholarship centre as a site for putting into practice Ranciere's theories of radical intellectual equality and a commitment to intellectual liberation. I also draw on Leanne Betasamosake Simpson's idea of land as pedagogy as a frame to reconsider knowledge creation and dissemination. My goal with this presentation is to create a space to ask the following questions: What should be the role of the academy in a society where the material conditions of its members have been met and the fundamental relationship is not based on exchange? Can the digital scholarship centre model non-oppressive organization approaches in the context of a research and learning institution? Digital scholarship centres, much like makerspaces in public libraries, have the potential to embody a commitment to public humanities. However, the very definition of the public good and disciplinarity will require an epistemological reframing in such a proposed utopian context.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.037 | 0.051 |
| Scholarly communication | 0.022 | 0.009 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.019 | 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".