Bibliographic record
Abstract
It is an honour, privilege, and pleasure to provide this foreword to Muiwlanej kikamaqki -Honouring Our Ancestors: Mi'kmaq Who Left a Mark on the History of the Northeast, 1680 to 1980 by Janet E. Chute and her colleagues.This volume is a compilation of painstaking research and documentation completed through the collaboration of Mi'kmaw and non-Mi'kmaw scholars, including Aboriginal university students who have worked under the guidance of Dr. Chute.It is an intriguing collection of factual historical information about Aboriginal leadership across Mi'kma'ki (the Atlantic Provinces, southern Quebec, and Maine) and the seven Mi'kmaw districts.From a Mi'kmaw perspective, this book is useful because it highlights historical genealogical issues by focusing on kinship connections among our families and these families' interrelationships with early settlers: Acadian, Planter, Germanic, and Loyalist.It gives the reader a clear view of the importance of family connections between the Mi'kmaq and the Acadians, as well as later settlers within Mi'kma'ki.It also provides an overview of the leadership of each district and attests to the consistent diplomacy that Mi'kmaw leaders practised with colonial officials.Dr. Elsie Charles Basque, to whom this book is dedicated, was the first Mi'kmaw person to graduate from the Nova Scotia Teachers College.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.390 | 0.350 |
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".