Note on Methodology and Sources
Bibliographic record
Abstract
Note on Methodology and SourcesA lthough a more detailed description of the methodology employed in this study is found in the Introduction, I thought it useful to provide additional information on the range of sources and the database approach used to organize an array of archival records.Dr. Frank Tough's research into the scrip claims of the Metis in northwestern Saskatchewan, work begun while he was at the University of Saskatchewan, inspired the doctoral work on which this book is based.Although my research focuses on the nature of Metis culture and society in northwestern Saskatchewan communities through an explication of historical genealogies, I adopted a database approach to records management in a manner encouraged by Dr. Tough.Reconstructing the genealogies for northwestern Saskatchewan's ancestral families required a large set of records from a variety of sources, including scrip applications; Hudson's Bay Company post records, such as journals, correspondence, censuses, post reports, and employment data; parish registries from Île à la Crosse, Portage La Loche (present-day La Loche), and Green Lake (also known as Lac Vert); and Canadian censuses from 1880, 1890, and 1901, and the 1906 prairie census.From his own research program, Dr. Tough graciously provided me access to the scrip applications and the 1880, 1890, and 1901 census records that he and a research team affiliated with the Matri-X project (Metis Aboriginal Title Research Initiative "X") gathered and databased.Both record groups are in the public record and available in a variety of locations, although the originals are housed at Library and Archives Canada (LAC) in Ottawa.I made several trips to LAC to view some
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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 | 0.139 | 0.323 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.016 | 0.024 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.008 | 0.012 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.124 | 0.065 |
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".