Evaluation of projections of populations for the aboriginal identity groups in Canada, 1996-2001
Bibliographic record
Abstract
The population projections for the Aboriginal identity groups (North American Indians, Métis and Inuit) by age and sex from 1996 to 2001 were developed at the Canada level, using the cohort-component method. The purpose of this paper is to compare and analyze the error of closure between the projected 2001 and adjusted 2001 population counts due to net census undercounts. It is observed that the error of closure for the 2001 projected Aboriginal population based on the 1996 adjusted census population seems to be lower by 7% over the 2001 Census adjusted Aboriginal population. In contrast, the projected populations for North American Indians and Inuit are lower by -0.20% and -2.73%. However, for the Métis the error of closure is extremely high, at -24.84%. Reasons for the higher error of closure for the Métis such as the effects of intra-generational ethnic mobility will be discussed in the paper.
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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 | 0.003 | 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 | 0.001 | 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".