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The Age and Time of No Retirement

2021· book-chapter· en· W3171881064 on OpenAlexaff
Adnan ul Haque

Bibliographic record

VenueAdvances in human services and public health (AHSPH) book series · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsYorkville University
Fundersnot available
KeywordsCollectivismPerspective (graphical)PacePopulation ageingPopulationDeveloped countrySample (material)Demographic economicsDeveloping countrySociologyEconomicsDevelopment economicsEconomic growthGeographyIndividualismDemographyMarket economy

Abstract

fetched live from OpenAlex

This comparative study considers global perspective by including developed and developing economies for exploring the social and economic impact of aging. Using stratified, purposive, and networking technique, the online opened-ended questions responses were gathered from the sample of 258. The findings confirmed that there is no age of retirement. Aging population contributions are significant and termed in this study as ‘knowledge-gem' (GK). The older population rate is increasing at a greater pace in the emerging economies in comparison to developed economies. Interestingly, the social activities remain constant in both types of economies. Post-retirement, elderly women are significant contributors to social activities while men have significant contribution to economic activities. From the cultural perspective, the aging population is mainly found in the ‘collectivism' on the grid-group cultural (GGC) model. The aging population is facing the challenges of in-equalities based on gender, class, and race in both developed and less-developed economies.

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)0.003
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: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.102
GPT teacher head0.391
Teacher spread0.289 · 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
GenreOther

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

Citations1
Published2021
Admission routes1
Has abstractyes

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