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Record W1893434933 · doi:10.25336/p6hs5g

Fertility in the Age of Demographic Maturity: An Essay

2010· article· en· W1893434933 on OpenAlexaffvenue
Anatole Romaniuk

Bibliographic record

VenueCanadian Studies in Population · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFertilityPopulationFinancial independenceTotal fertility rateOld Age SecurityEconomicsSalaryWelfareMaturity (psychological)Economic growthLabour economicsBirth rateDevelopment economicsDemographic economicsSociologyPolitical scienceMarket economyFamily planningFinanceDemography

Abstract

fetched live from OpenAlex

As humanity is moving into a new age of its demographic evolution, I call it demographic maturity, the emerging demographic configurations – generational sub-replacement fertility, advanced aging and potential population implosion – call for new ways of thinking about population and new policy approaches. While we live longer and healthier, we also reproduce less and less. We are stuck in a culture of low fertility. The strong motivations for foregoing motherhood are financial: a two-salary wage is better than one even for the higher middle class. No less important is the woman’s financial independence in a societal environment where marriage as an institution is under considerable stress. Motherhood is to be rewarded adequately for its highly important social role and it has to be sufficient to reassure potential mothers of their financial concerns. What is required is a more balanced resource allocation between production and reproduction. The old welfare type hand-outs like child bonuses do not work. Societies, particularly the rich, ought to realize that to raise fertility, even to generational replacement level, not only is a much greater financial effort called for but some of the tenants of the liberal economy need to be put into question to make room for social concerns such a renewal of generations, if they want to survive as national entities. This essay advocates a stationary population as the best response to challenges such as ecological health, national identity and cohesion, and possibly world peace.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.060
GPT teacher head0.349
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2010
Admission routes2
Has abstractyes

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