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El impacto de la política en la salud

2007· article· es· W2121664730 on OpenAlexaff
Vicente Navarro, Carme Borrell, Carles Muntañer, Joan Benach, Águeda Quiroga, Maica Rodríguez‐Sanz, Jordi Gumà, Núria Vergés Bosch, M. Isabel Pasarín

Bibliographic record

VenueSalud Colectiva · 2007
Typearticle
Languagees
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLife expectancyPoliticsInfant mortalityWelfareWelfare economicsInequalityWelfare statePower (physics)Demographic economicsVariablesDemographySociologyDeveloping countryPolitical scienceEconomicsEconomic growthStatisticsPopulation

Abstract

fetched live from OpenAlex

The objective of this article is to report on the findings of a study that analysed the impact of politics on infant mortality and life expectancy in countries of the Organization for Economic Cooperation and Development from 1950 to 1998.Countries were grouped by political tradition based on the parties that governed in these countries from 1950 to 1998. Infant mortality and life expectancy at birth were the dependent variables. Independent variables were grouped on political power, labour market, welfare state and income inequalities. It is presented a descriptive analysis of all variables by political tradition and also Pearson correlation coefficients between variables in different periods.The main conclusion of the study is that the duration of pro-redistributive governments is related with the reduction of income inequalities and infant mortality.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.017
GPT teacher head0.478
Teacher spread0.460 · 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 designNot applicable
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

Citations5
Published2007
Admission routes1
Has abstractyes

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