Bibliographic record
Abstract
While the following article is based on Rebecca Ingalls’s research on teen literacy practices in the United States, it reflects many issues at stake in the Canadian context. Reading Ingalls’s work, I felt a great deal of affinity with her research, as much of what she documents here resonates with my own experience of working with young spoken-word artists in Vancouver and Edmonton. My research on the practices of spoken-word artists in Canada indicates that most contemporary spoken-word artists get their first taste of the art form early in life. Many young artists are exposed to spoken word at school, via spoken word / performance poetry / storytelling outreach programs like the “Poets in the Schools” initiatives run by the League of Canadian Poets and the Calgary International Spoken Word Festival, which have grown in popularity in recent years. The sense that spoken word is an accessible medium even (especially) for students who are not typically engaged by page poetry is pervasive in spoken-word scenes, and socially conscious spoken-word artists/ activists often use the medium as a way to encourage youth from marginalized communities and / or “at risk youth” to raise their voices and share their experiences. What is increasingly significant about the accessibility of the spoken-word scene in small and large Canadian cities is the relative ease with which young people can now take their work from their high school Writers’ Craft or Language Arts classrooms to an open mic in a cafe, to a poetry slam, to an all-ages show, to being hooked for other cabaret shows and/or producing their own shows. The fact that most cities now have an established spoken-word scene with a range of minor-friendly venues makes it possible for young people to easily participate and to create their own niches.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".