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Record W2345781320 · doi:10.6000/1929-7092.2016.05.11

The Long-Run Relationship among Health and Income in Mexico, 1940-2011

2016· article· en· W2345781320 on OpenAlexvenueno aff
Vicente Germán–Soto

Bibliographic record

VenueJournal of Reviews on Global Economics · 2016
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
FundersUniversidad Autónoma de Coahuila
KeywordsNoveltyEconomicsPer capita incomeDemographic economicsPer capitaGovernment (linguistics)Development economicsEconometricsDemographyPsychologySociology

Abstract

fetched live from OpenAlex

Theoretically, it has been argued the existence of not only a strong positive correlation among health and real per capita income, but also that their variations are highly interconnected. The stationarity among health indicators and income is analyzed for Mexico, allowing for the presence of multiple structural breaks along 1940-2011, with the aim to study its long-run relationship and how the reductions of the public expenditure have affected this link. One novelty is the long-run perspective supported on structural breaks that affect both the level and the slope of the time series. After the serial correlation is accounted for, several stationary processes evolving around a broken trend are found. The estimated breakpoints are widely related to events as crises and health system reforms, while the corresponding regimes changes lead to a stage of minor health expenditure. This last can be of concern to government and society if improvements on health and economic development are desired.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.089
GPT teacher head0.427
Teacher spread0.338 · 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 designObservational
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
Published2016
Admission routes1
Has abstractyes

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