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Record W2596590837

Four perspectives on population policies

2014· article· en· W2596590837 on OpenAlexaff
Urs P. Thomas

Bibliographic record

VenueInternational Journal of Environment and Pollution · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPopulationContext (archaeology)Perspective (graphical)Economic growthBlameSustainable developmentEmpowermentSolidarityPolitical scienceRhetoricDevelopment economicsSociologyPolitical economyEconomicsGeographyPoliticsSocial psychologyLawPsychology
DOInot available

Abstract

fetched live from OpenAlex

This policy study placed population policies into the wider context of North–South relations and sustainable development policies by presenting four perspectives regarding this topic: The Lipservice for Solidarity Perspective is characterized by well–meaning pledges and rhetoric by industrialized countries, but it lacks a serious follow–up; The Blame the Rich Perspective puts too much emphasis on individual women's reproductive rights and industrialized countries' policy failures, while it tends to overlook ancient local constraints on women's empowerment, which are rooted in cultural and socioeconomic behavioural patterns and make exercising women's rights illusory; The Sustainable Development Perspective is considered to be on the right track, but population priorities tend to get lost among many other objectives; The Intergenerational Perspective is seen as the preferred analytical framework, because it focuses on collective aspects of the development process, and on the ecosystem's carrying capacity.

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)0.008
metaresearch head score (Gemma)0.008
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0050.015
Scholarly communication0.0110.009
Open science0.0020.008
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0090.001

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 head0.016
GPT teacher head0.273
Teacher spread0.257 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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