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Record W7154044351 · doi:10.65748/fiqf-2010-0015

WEALTH OF THE NATIONS MEASUREMENT METHODS IN THE FACE OF CHANGING GLOBAL SOCIAL-ECONOMIC ENVIRONMENT

2024· article· W7154044351 on OpenAlexfundno aff
Krzysztof Opolski, Tomasz Potocki

Bibliographic record

VenueFinancial Internet Quarterly · 2024
Typearticle
Language
FieldSocial Sciences
TopicPublic health and occupational medicine
Canadian institutionsnot available
FundersUnited Nations University World Institute for Development Economics ResearchDalhousie University
KeywordsMultidisciplinary approachFace (sociological concept)Work (physics)Field (mathematics)Social securityGlobal South

Abstract

fetched live from OpenAlex

One of the main debates in economics concerns the analysis of the global wealth. Economics became multidisciplinary research field which includes achievements of psychology, neurology, ethics and social science. As a result, the GDP should increasingly become multi-polar indicator. Alongside this work authors underline growing recognition of the importance of other contributions to individual global wealth, most especially psychology factors, health status, IQ, environment, personal security and aspects of CSR.

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)0.040
metaresearch head score (Gemma)0.095
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.095
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0100.010
Science and technology studies0.0020.002
Scholarly communication0.0050.005
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.050
GPT teacher head0.390
Teacher spread0.340 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations0
Published2024
Admission routes1
Has abstractyes

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