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Record W4392875795 · doi:10.4324/9781032710235-11

Primary Social and Health Services for the Aged in Greece

2024· book-chapter· en· W4392875795 on OpenAlexaboutno aff
A.S. Dontas

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessGerontologyMedicine

Abstract

fetched live from OpenAlex

The demographic history of modern Greece over the past 125 years can be divided into three periods: A period of mounting population pressure and limited resources between 1860 and 1912 resulting in a mass migration of youth to the United States and thus an early maturity of the country around the turn of this century. A brief period of rapid territorial expansion and parallel population changes as a result of a long war, which started successfully in 1912 only to result ten years later in a national catastrophe without precedent in Greece’s 3,000 years’ history. About one and one-half million refugees forcibly evicted from Asia Minor were re-settled within a few months in a country whose population barely exceeded 4.5 million. As a consequence, a relative demographic rejuvenation resulted, but since poverty and political instability persisted emigration continued unabated until shortly before World War II. A post-War period of progressive demographic maturity followed by an explosive demographic ageing related to large scale emigration to Western Europe, Canada, and Australia and simultaneous internal migration to metropolitan areas. The internal migrants raised small families of one or two children, resulting in an arrested population growth. Presently Greece occupies a prominent position, as one of the less industrialised and the fastest ageing countries in the developed world.

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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.057
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0570.011

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 head0.119
GPT teacher head0.475
Teacher spread0.356 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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