From the White Horse Plain to the shores of Lake Manitoba: migration stories of my maternal Metis family the Brelands, Naults/Neaults, Thiberts, and Zaces/Zastres.
Bibliographic record
Abstract
The socioeconomic and cultural beginnings of the Metis are found within family, extending outward through kinship networks or kinscapes created and maintained to connect families and communities to each other across distances (Lakomaki 2014 in St-Onge and Macdougall 2021, 90). Mobility and migration were both familiar and necessary elements of Metis life. Scholar Chris Anderson (2014) described his own historic self-understanding of being Metis “as a form of memory and nostalgia rooted in the people, places, and events tied to a core of Metis peoplehood, despite its widespread marginalization in contemporary white society” (270). Utilizing genealogical reconstructions and ancestor biographies, this thesis recounts the migration stories of the Breland, Nault/Neault, Thibert, and Zace/Zastre families from which I am a direct descendent. It examines and describes the precolonial beginnings of these Metis families, their early presence on the lands of the northern plains and northwest, their migration to the Red River Settlement, and their subsequent dispersal to the western shores of Lake Manitoba where they established the communities of Ste. Rose du Lac and Cayer. The work is framed by two Indigenous studies frameworks, Wahkootowin (Macdougall 2010; Wildcat 2018; Campbell 2007) and Insurgent Research (Adam Gaudry 2011). Key concepts that provide context for each family’s story include relationality (Moreton-Robinson 2017; Wildcat & Voth 2023), peoplehood (Andersen 2014; Hancock 2021), nationhood (Andersen 2014), and community (Stevenson 2020; Hogue 2015, Andersen 2014).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.012 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".