Annual Demographic Statistics, 2004 [Canada] [Excel]
Bibliographic record
Abstract
<p>Annual Demographic Statistics contains the following data: population estimates by age and sex for Canada, the provinces, territories, census divisions and census metropolitan areas; estimates by age, sex and marital status for the provinces and territories; and estimates of the number of census families for Canada, the provinces and territories, by type of family (husband-wife, lone-parent), size of family, age of children and age and sex of parents. It also includes statistics for the demographic components that were used to produce the population estimates (births, deaths, marriages, divorces, immigration, total emigration, internal migrations and non permanent residents) by age and sex. In addition, there are highlights of current demographic trends and a description of the methodology; population data from 1971 for provinces and territories, and from 1986 for census divisions and census metropolitan areas; and animated age pyramids, which illustrate the aging of the population.</p> <p>Continued by <a href=" https://search1.odesi.ca/#/search/_term_term=Demographic%2520Estimates%2520Compendium&type:3;&fromDate=Earliest&toDate=Present&refineColl_all:true&cora:true&icpsr:true&dlimf:true;&refineOdesi_all:true&statCaMicro:true&statCaAgg:true&pop:true&other:true;&addTerms@;&page:1" target="_blank">Demographic Estimates Compendium</a>.</p> <p><a href="http://odesi.scholarsportal.info/documentation/ads/2004/ads2004.html" target="_blank">Access data here</a></p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".