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The Age and Time of No Retirement

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

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.102
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