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Record W1999773006 · doi:10.1111/1467-6303.00090

'Facilitating' globalization processes: Financial technologies and the World Bank

2002· article· en· W1999773006 on OpenAlexaff
Dean Neu, Elizabeth Ocampo-Gómez, Omar García Ponce de León, Margarita Flores Zepeda

Bibliographic record

VenueAccounting Forum · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicGlobalization and Cultural Identity
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsGlobalizationAgency (philosophy)BusinessFinancial globalizationTRACE (psycholinguistics)Chinese financial systemField (mathematics)FinanceFinancial systemAccountingEconomicsPolitical scienceMarket economySociologyChina

Abstract

fetched live from OpenAlex

This article examines how the World Bank operates as a coordinating agency within the field of higher education and how its specific financial technologies operate as the carriers of globalization practices. By focusing on organizations such as the World Bank, we can identify and trace the mechanisms through which globalization practices are diffused. We do so by identifying and discussing the three main activities used by the World Bank to wield its authority and influence: lending, technical assistance, and the publication of reports.

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)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0050.020
Scholarly communication0.0160.014
Open science0.0010.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.013
GPT teacher head0.263
Teacher spread0.250 · 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.

Study designQualitative
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

Citations11
Published2002
Admission routes1
Has abstractyes

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