Poetic Fabulations: Chartering Relationalities of Black Flourishing, Mutuality, Inclusive Excellence, and Accountability
Bibliographic record
Abstract
This collective work (four authors) demonstrates how persistent structures in higher education are mobilized in the signing of the Scarborough Charter on Anti-Black Racism and Black Inclusion in Canadian Higher Education: Principles, Actions, and Accountabilities. We read this event against the grain, as an act requiring relation-building and accountability. Recognizing the promises and risks of this work, and inspired by Black Feminist/coalitional practices which disorient from pre-mapped routes and knowledges in universities and reorient to otherwise ways of being, we name this process “poetic fabulation.” We begin with poetry and proceed with seven stanzas that orient thematic reflections in each prose section that follows. The multi-vocality of the piece gives evidence to the experiences of the authors in this work. The interregnum which follows stanza 4, functions at the simultaneous and unruly registers of poetry, analysis, affect, and the somatic, to interrupt the flow, signalling how we experience labouring within the academy. Our work is collaborative, but also entails being hailed and responding in different ways. Using a full spectrum of creative and analytic skills, we navigate towards shared goals to process what we witness in and across post-secondary institution(s), to hold and care for the impacts of discretionary power.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.036 | 0.094 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".