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Record W3211815191 · doi:10.5195/aa.2021.330

Planning for Old Age in Peru: Count on Kin or Court the State?

2021· article· en· W3211815191 on OpenAlexaff
Susan Vincent

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsReciprocity (cultural anthropology)LivelihoodPovertyOddsCash transfersCashPensionState (computer science)Economic growthDemographic economicsPolitical scienceEconomicsBusinessSociologyGeographyLogistic regressionMedicineFinanceAgriculture

Abstract

fetched live from OpenAlex

Reciprocity among kin is central to Peruvian livelihoods, including into old age. Potentially affecting such family support, since 2011 Peru has offered a non-contributory cash transfer called Pensión 65 for seniors living in poverty. Past negative experiences of state assistance, the limited sum, uncertainty about eligibility rules, and surveillance of recipients are weighed against the regularly paid income. This case study provides insight into how Allpachiqueños strategize about livelihood across generations. It shows that, when children have prospects, parents will jeopardize their access to Pensión 65 (for example, by co-signing loans), as they prioritize material reciprocity. In contrast, in families with the fewest resources, parents spare their children from supporting them economically and do all they can to ensure eligibility by foregoing their assistance and withdrawing from active work. This forced retirement reflects their understanding of the state’s rules of the fund and is at odds with local practice. This research addresses the recent trend for countries of the Global South to offer cash transfers to older individuals by examining the implications of the terms of eligibility.

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)0.002
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.002
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.253
GPT teacher head0.558
Teacher spread0.305 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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