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Record W2754486029 · doi:10.1177/0309132517739142

The geographies of social finance: Poverty regulation through the ‘invisible heart’ of markets

2017· article· en· W2754486029 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

VenueProgress in Human Geography · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCapitalismPovertyGeography of financeSocial studies of financeTypologyPrivate finance initiativeFinanceEconomicsFinancial marketSociologyPolitical scienceEconomic growthPrivate sector

Abstract

fetched live from OpenAlex

The global financial and anti-poverty industries are embracing an investment philosophy called social finance, which claims that private profit-making can create positive benefits for society. Attempting to resolve the problems of capitalism from within the system, social finance reframes finance as a force for engendering, rather than disrupting, the public good. This article argues that social finance raises theoretical concerns for geographical research on finance, poverty, and neoliberalizing capitalism. I outline a typology of social finance’s forms and propose a geographical research agenda, arguing that social finance practitioners’ simplistic framings of geography belie many other geographies that constitute what is both an emerging financial marketplace and a logic of poverty regulation.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score1.000

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.037
GPT teacher head0.292
Teacher spread0.255 · 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