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Health Care for Older Persons in Colombia: A Country Profile

2009· article· en· W1602443110 on OpenAlexaff
Fernando Gómez, Carmen‐Lucía Curcio, Gustavo Duque

Bibliographic record

VenueJournal of the American Geriatrics Society · 2009
Typearticle
Languageen
FieldMedicine
TopicAging, Health, and Disability
Canadian institutionsUniversité de Sherbrooke
FundersUniversidad de Caldas
KeywordsLife expectancyMedicineHealth careDeveloping countryPopulationGerontologyUnemploymentQuality of life (healthcare)PovertySocioeconomicsEnvironmental healthEconomic growthNursing

Abstract

fetched live from OpenAlex

Colombia is a country of approximately 42 million inhabitants, with some 2.5 million being aged 65 and older. Currently, life expectancy in Colombia is 72.3. By 2025, the population life expectancy at birth will be 77.6 for women and 69.8 for men. The quality of care that people receive as they age in Colombia varies according to where they live. Individuals living in the highly urbanized areas of Colombia receive high-quality care, whereas elderly subjects living in rural areas and in the southern and northern regions are exposed to unemployment, low income, inequity of access to health care, drug trafficking, and armed conflict. In spite of these problems, characteristics of aging of older people in terms of functionality and healthcare access are similar to those of people living in developing countries around the world. This article reviews the particular characteristics of the elderly population in Colombia, especially the significant changes that have happened in recent years, when social instability and conflict have determined that health resources be redirected to other budget priorities such as defense and security.

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)0.000
metaresearch head score (Gemma)0.001
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: Review · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.010
GPT teacher head0.319
Teacher spread0.310 · 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
GenreReview

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

Citations35
Published2009
Admission routes1
Has abstractyes

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