Bibliographic record
Abstract
Mawopiyane, in Passamaquoddy, literally means "let us sit together, " but the deeper meaning is of a group coming together, as in the longhouse, to struggle with a sensitive or divisive issue.The word indicates an urgency to meet because the outcome is something very desirable, such as resolving a conflict or bringing about peace.It's a healing word.We, the Wabanaki members of the group that guided this project, chose this word to describe those of us who came together to create this book.Mawopiyane is a word that is recognizable in all Wabanaki languages, and it reflects the collaborative nature of our effort.In those long-ago Gatherings, and again in co-creating this book, our commitment has been to aid one another in navigating through the hundreds of years of malfeasance, genocide of Indigenous peoples, and theft of homelands that has occurred in both the United States and Canada under the pretense of law.In the Gatherings, we re-enacted the form of treaty-making that existed among our peoples before the arrival of the European invasion.Our treaties between and among our Nations enabled the making of relatives and included all Living Beings.Indigenous Nations extended this form of treaty-making to the incoming Europeans and the establishment of their settlements, but ultimately those treaties were broken.Our
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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 | 0.001 | 0.005 |
| 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) | 0.455 | 0.262 |
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".