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Record W1959820229 · doi:10.1177/0170840615585334

Multiple Paths to Institutional-Based Trust Production and Repair: Lessons from the Russian Bank Deposit Market

2015· article· en· W1959820229 on OpenAlexaff
Andrew Spicer, Ilya Okhmatovskiy

Bibliographic record

VenueOrganization Studies · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsMcGill University
Fundersnot available
KeywordsPropositionState (computer science)BusinessProduction (economics)State ownershipGovernment (linguistics)PoliticsCashAccountingControl (management)Test (biology)Market economyEconomicsIndustrial organizationFinancial systemFinanceEmerging marketsMicroeconomicsLawPolitical scienceManagement

Abstract

fetched live from OpenAlex

We propose and test the proposition that state ownership represents an important mechanism of institutional-based trust production in market development that requires analysis in its own right, particularly following periods of financial crisis when the state’s role as a regulator is often viewed as ineffective or corrupt. To test the proposition that state ownership and state regulation act as distinct sources of institutional-based trust production, we examine individual choices of market participation and avoidance in Russia’s market for bank deposits. To analyze the consequences of institutional-based trust, we look at individual preferences to keep savings in a private bank, in a state bank, or in cash outside of the banking system. To analyze antecedent conditions, we measure an individual’s trust in political actors and government agencies. Our results support the proposition that the state produces institutional-based trust in the Russian banking system through its roles as both an owner and a regulator.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.043
GPT teacher head0.247
Teacher spread0.204 · 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 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

Citations35
Published2015
Admission routes1
Has abstractyes

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