Bibliographic record
Abstract
In reading this historic chronicle of the painful poverty among the Cree in James Bay, Ontario, Canada, I keep thinking how incredible it is that a member of parliament could care so much about his constituency and devote so much of his time to helping the beautiful people of the land of the Cree and Ojibway in sub-Arctic country."-AlAnisObOmsAwin, filmmAker "Shannen Koostachin knew First Nations students were dropping out of her school in Attawapiskat because 'It is hard to think you will grow up someone important when you don't have resources like libraries and science labs … we are not going to give up and we want our younger brothers and sisters to go to school thinking school is a time for hopes and dreams of the future-every kid deserves this.' "As a child inspired by Shannen said, 'Childhood does not wait around for politicians to do the right thing,' and so thousands of children joined together to write letters to the government demanding a proper education for all First Nations students.The Prime Minister's mailbox began filling up with letters made with crayons and sparkles, and the largest child-led rights campaign in Canadian history was born."In this must-read book, Charlie Angus shares Shannen's inspiring journey from a child going to school in run down trailers next to a toxic waste dump to one of 45 children in the world nominated for the International Children's Peace Prize.Shannen did everything in her power to ensure First Nations children would get the proper education they deserve, and after reading this book you will, too."-CindyblACkstOCk, first nAtiOns Child And fAmily CAring sOCiety Of CAnAdA
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.014 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".