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Boats and Tides and “Trickle Down” Theories: What Economists Presume about Wellbeing When They Employ Stochastic Process Theory in Modeling Behavior

2012· article· en· W2147979458 on OpenAlex

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

VenueEconomics · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsClubPovertyEconomicsPer capitaConvergence (economics)Polarization (electrochemistry)InequalityDistribution (mathematics)Positive economicsDevelopment economicsPublic economicsEconometricsNeoclassical economicsSociologyMacroeconomicsEconomic growthMathematicsDemography

Abstract

fetched live from OpenAlex

Abstract Aphorisms that “rising tides raise all boats” or that material advances of the rich eventually “trickle down” to the poor are really maxims regarding the nature of stochastic processes that underlay the income/wellbeing paths of groups of individuals. This paper looks at the implications for the empirical analysis of wellbeing of conventional assumptions regarding such processes which are employed by both micro and macro economists in modeling economic behavior. The implications of attributing different processes to different groups in society following the club convergence literature are also discussed. Various forms of poverty, inequality, polarization and income mobility structures are considered and much of the conventional wisdom afforded us by such aphorisms is questioned. To exemplify these ideas the results are applied to the distribution of GDP per capita in the continent of Africa.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
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 studies0.0000.000
Scholarly communication0.0010.003
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 head0.024
GPT teacher head0.226
Teacher spread0.202 · 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