Bibliographic record
Abstract
Historically, birth rates in Alberta have followed closely the trajectory of change experienced by the other Canadian provinces. Its total fertility rate fell during the low point of the 1930s; it increased during the post-War baby boom in the 1950s and sixties, and thereafter fell to subreplacement levels beginning in the mid 1970s. In recent years, especially since the early 2000s, the birth rate in Alberta has unexpectedly increased, such that by 2007, it had reached 1.90 children per woman - not far from the 2.1 level needed for generational replacement in the long term. During this same period both national and provincial fertility rates fluctuated at levels below those of Alberta (except Saskatchewan and Manitoba, whose rates have been higher). In this study, I examine the historical pattern of fertility change in Alberta, noting similarities and differences with the other provinces. I then look at the association of selected macro level factors (marriage, unemployment, wages, female labour force participation) with change in total and parity-specific birth rates between 1997 and 2007, a period of unprecedented economic growth in Alberta. The statistical results show that although marriage is not significantly correlated with change in fertility rates, male and female wages and female labour force participation all show associations consistent with a procyclical interpretation of fertility change - that is, periods of economic growth are conducive to fertility increase whereas bad economic times are associated with reduced fertility.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".