The Demographic Situation in France: Recent Developments and Trends over the Last 70 Years
Bibliographic record
Abstract
On 1 January 2015, the population of France was 66.3 million (of which 64.2 million in metropolitan France), an increase of 0.45% with respect to the previous year. Fertility increased slightly, to 2.0 children per woman. Women had children at a mean age of 30.2 years, and men at 33.1 years. Nearly six in ten children were born outside marriage. Net migration remained quite stable. Among residence permits issued to migrants in 2013, half were granted for family reasons, slightly less than a quarter for educational purposes, 10% for humanitarian reasons, and 7% for work-related reasons. The number of marriages (among opposite-sex couples) continued to decrease slightly. Marriage was opened to same-sex couples on 17 May 2013. Between that date and the end of 2014, 17,000 same-sex marriages were registered. The seasonality of marriages remained fairly stable, while the annual peak in civil partnerships (PACS) previously observed in the second quarter shifted to the end of the year. Mean age at marriage continued to increase, reaching 34.6 years for women and 37.2 years for men in 2013. According to provisional estimates, the number of deaths in 2014 totalled 559,300. Women’s life expectancy was 84.7 years and that of men was 79.2 years, a gap of 5.5 years that has been narrowing over time.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".