Estimating Lactase Nonpersistence Distributions in the Multi-Ethnic Canadian Demographic: A Population-Based Study
Bibliographic record
Abstract
OBJECTIVES: The lactase persistence/nonpersistence (LP/LNP) phenotypes follow a geographic pattern that is rooted in the gene-culture coevolution observed throughout the history of human migrations. The immense size and relatively open immigration policy have drawn migrants of diverse ethnicities to Canada. Among the multicultural demographic, two-thirds of the population are derived from the British Isles and northwestern France. A recent assessment of worldwide lactase distributions found Canada to have an LNP rate of 59% (confidence interval [CI] 44%-74%). This estimate is rather high compared with earlier reports that listed Canada as a country with a 10% LNP rate; the authors had also noted that biases were likely because their calculations were based largely on Aboriginal studies. We hereby present an alternate LNP prevalence estimate at the national, provincial and territorial level. METHODS: We applied the referenced LNP frequency distribution data to the 2016 population census to account for the current multi-ethnic distributions in Canada. Prevalence rates for Canada, the provinces and territories were calculated. RESULTS: The national LNP rate is estimated at 44% (CI 41%-47%) after accounting for the 254 ethnic groups, with the lowest rates found in the eastern provinces and the highest rates in the Northwest Territories (57%) and Nunavut (66%), respectively. CONCLUSION: Despite the heterogeneous nature of the referenced data and the inference measures taken, evidently, the validity of our LNP estimate is anchored on the inclusion of multi-ethnic groups representing the current Canadian demographic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".