Genealogical Analysis of Maternal and Paternal Lineages in the Quebec Population
Bibliographic record
Abstract
The Quebec population is one of the rare populations of its size for which genealogical information is available for an uninterrupted period of almost four centuries. This allows for in-depth studies on the formation and evolution of a young founder population. Using data from two major population registers, in this study we focus on the maternal and paternal lineages (i.e., strictly female or male genealogical lines) that can be traced back within the Quebec genealogies. Through the analysis of these lineages it is possible to characterize the founders who transmitted to the contemporary population their mitochondrial (for females) and Y-chromosome (for males) DNA. The basic material consists of 2,221 ascending genealogies of subjects who married in the Quebec population between 1945 and 1965. On average, more than nine generations of ancestors were identified among the lineages. Analyses of maternal and paternal lineages show that the number of paternal founders is higher and their origins and genetic contributions are more variable than that of maternal founders, leading to a larger effective population size and greater diversity of Y chromosomes than of mtDNA. This is explained for the most part by differential migratory patterns among male and female founders of the Quebec population. Comparisons of sex-specific genetic contributions with total genetic contribution showed a strong correlation between the two values, with some discrepancies related to sex ratio differences among the founders' first descendants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".