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Record W4399047700 · doi:10.1002/pop4.398

A rising tide that lifts all boats: Long‐term effects of the Alaska Permanent Fund Dividend on poverty

2024· article· en· W4399047700 on OpenAlexfundno aff
Matthew Berman

Bibliographic record

VenuePoverty & Public Policy · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
FundersYork University
KeywordsDividendTerm (time)EconomicsPovertyFinanceEconomic growth

Abstract

fetched live from OpenAlex

Abstract Although not designed as a social program to redistribute income, the Alaska Permanent Fund Dividend (PFD) has been reducing poverty by providing equal annual payments to nearly all state residents for over 40 years. We examine direct effects of the PFD on Alaska poverty rates since 1990, using US Census and American Community Survey Public Use Microdata Sample records to adjust for under‐reporting of children's PFD income in official statistics. We estimate that the PFD reduced the number of Alaskans with incomes below the US poverty threshold by 20%–40%. We measure only a small effect on income distribution: a 0.02 reduction in the Gini coefficient. The effect of the PFD has been even larger for vulnerable populations. The PFD has reduced poverty rates of rural Indigenous Alaskans from 28% to less than 22%, and has played an important role in alleviating poverty among seniors and children. Aside from the special case of 2020, up to 50% more Alaska children—15% instead of 10%—would be living in poor families without PFD income. The poverty‐ameliorating effects of the PFD have lessened somewhat since 2000, as dividend amounts adjusted for inflation have been declining.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.052
GPT teacher head0.259
Teacher spread0.207 · 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.

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
Published2024
Admission routes1
Has abstractyes

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