Bibliographic record
Abstract
One bitterly cold night in the Winnipeg winter of 1999, I visited some friends who were having a small party at their home.Their living room was filled with people I didn't know -everyone was talking and laughing and I felt shy and out of place.As I got my bearings I spotted someone else who looked as if he didn't know many people there either.Louis Bird was quietly watching everything that was happening around him.We started talking and I noticed how closely he listened to the things I said and how easy it was to make him smile.Then we started talking about music and how important it is to each of us and Louis mentioned that he had brought his violin along.He took up his instrument and I sat down at the piano -and we became friends for life.Louis Bird is many things -a storyteller, a scholar, a musician, and an artist with words.For over forty years he has gathered the memories and stories of Omushkego (Swampy Cree) elders in communities along western Hudson and James Bays.He has crafted their legends and tales into an oral history of his people and his work conveys, as do great histories, the forces that moved and shaped his ancestors -the saga of the Omushkego Crees.Louis was born on a trapline in the bush near Winisk, Ontario, in 1934, part of an Omushkego community whose people still hunted and fished, still traded furs -and who had adopted the
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.588 | 0.406 |
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".