Bibliographic record
Abstract
My spoken word arises from Anishnaabek art, literary and oratory traditions and practices that encompass songs, chants, oratory, storytelling, poetry, speeches, stories and music as well as other art forms, both old and new. Some of the non-traditional or newer forms of Anishnaabek art that influence and inspire my work as a spoken word artist include jazz, hip-hop, rap, dance, media arts and, even more, the fusion of Anishnaabek arts with the arts and cultures of other Indigenous peoples as well as the many arts and cultures around us. As an artist, I am heavily influenced by my immediate environment — the people, places and natural/supernatural world that surrounds me. My spoken word did not develop from within the spoken word genre, nor has it been much influenced by any other spoken word. For me, “spoken word” was a natural progression in my work, a way of creatively expressing myself in a way that made sense to me and came about spontaneously as a result of what I was already doing, what I knew and who I am.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".