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Record W2929932278 · doi:10.1257/aer.20190098

Can Policy Change Culture? Government Pension Plans and Traditional Kinship Practices

2021· article· en· W2929932278 on OpenAlexaff
Natalie Bau

Bibliographic record

VenueAmerican Economic Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsKinshipPensionIncentiveGovernment (linguistics)Investment (military)Test (biology)Culture changeBureaucracyPublic policyEconomic growthBusinessEconomicsPolitical scienceSociologyMarket economyFinanceSocial scienceLawPolitics

Abstract

fetched live from OpenAlex

Policies may change the incentives that allow cultural practices to persist. To test this, I study matrilocality and patrilocality, kinship traditions that determine daughters’ and sons’ post-marriage residences, and thus, which gender lives with and supports parents in their old age. Two separate policy experiments in Ghana and Indonesia show that pension policies reduce the practice of these traditions. I also show that these traditions incentivize parents to invest in the education of children who traditionally coreside with them. Consequently, when pension plans change cultural practices, they also reduce educational investment. This finding further demonstrates that policy can change culture. (JEL G51, I20, J15, J16, J32, Z13)

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.958
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

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

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 head0.073
GPT teacher head0.340
Teacher spread0.266 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations48
Published2021
Admission routes1
Has abstractyes

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