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Record W2332909807 · doi:10.1080/17530350.2015.1135472

Peer lending and the subsumption of the informal

2016· article· en· W2332909807 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Cultural Economy · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
FundersUniversity of TorontoSocial Sciences and Humanities Research Council of CanadaUniversity of Arizona
KeywordsMainstreamAgency (philosophy)Financial servicesSociologyCredit scoreFinancializationFinanceEconomicsQualitative researchBusinessSocial sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

The informal financial practices of financially ‘excluded’ groups in the United States are being enrolled in a regulatory project to make new markets and produce financially self-sufficient subjects on the edges of the financial system. Drawing on mixed-methods qualitative research working with nonprofits in the San Francisco Bay Area, this paper explores how informal rotating savings and credit associations (ROSCAs) are being repurposed and formalized to make the risks of financially excluded groups legible, tractable and priceable for ‘mainstream’ financial service providers. In so doing, the paper explores how the credit score orders practices and relations that are ‘outside’ of the ‘financial mainstream’. While others have documented how the efforts of NGOs to marketize and commodify the social networks and cultural practices of the poor result in forms of dispossession, this is not what my research finds. Instead, I show how formalized ROSCAs are redistributing calculative agency, and enabling financially underserved groups to exert strategic control over the calculation of their credit scores.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score0.140

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.217
Teacher spread0.192 · 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