Learning for Liberation: Critical Black Poetry Pedagogy and Transformative Education
Bibliographic record
Abstract
This portfolio examines and employs Black poetry as a powerful strategy for liberation; it is both a sustained discussion of the principles and practices behind the teaching of poetry for emancipatory education and Black liberation, and a toolkit for educators. It specifically addresses Black youth in Toronto. It contains four main offerings addressed to three different audiences: 1. Learning for Liberation: Critical Black Poetry Pedagogy And Transformative Education, "If We Ruled the World": A critical essay which argues that improving the quality of life for marginalized bodies, means highlighting the importance of Arts Education and providing insight into how the black experience may be re-imagined through poetry. 2. Poetry Saved My Life: Winning the Race! A Militant Black Poetry Teacher's Guide for Social Change: is a Popular Education Toolkit intended to aid first generation Black Canadian youth in the successful navigation of culturally-insensitive/hostile learning environments and racist workspaces. 3. Re-Imagining the Black Experience Through Word-Sound-Power: is an audio recording on traumatic/racialized historical violence and memory; intended to disrupt the dominant discourse on race relations. 4. Poetry Saved My Life! A Black PoeTree Experience (Series): A collection of short and long poems intended as social commentary on racial issues, within a North American context.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.023 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".