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Record W1552002249 · doi:10.1017/s0047279413000573

In the Shadow of the Welfare State: The Role of Payday Lending in Poverty Survival in Australia

2013· article· en· W1552002249 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Social Policy · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsVictoria Park
Fundersnot available
KeywordsPovertyWelfareShadow (psychology)WorkfareWelfare stateSocial policyEconomicsCorporate governanceMainstreamDevelopment economicsEconomic growthPolitical scienceMarket economyFinancePolitics

Abstract

fetched live from OpenAlex

Abstract A defining characteristic of contemporary welfare governance in many western countries has been a reduced role for governments in direct provision of welfare, including housing, education, health and income support. One of the unintended consequences of devolutionary trends in social welfare is the development of a ‘shadow welfare state’ (Fairbanks, 2009; Gottschalk, 2000), which is a term used to describe the complex partnerships between state-based social protection, voluntarism and marketised forms of welfare. Coupled with this development, conditional workfare schemes in countries such as the United States, Canada, the UK and Australia are pushing more people into informal and semi-formal means of poverty survival (Karger, 2005). These transformations are actively reshaping welfare subjectivities and the role of the state in urban governance. Like other countries such as the US, Canada and the UK, the fringe lending sector in Australia has experienced considerable growth over the last decade. Large numbers of people on low incomes in Australia are turning to non-mainstream financial services, such as payday lenders, for the provision of credit to make ends meet. In this paper, we argue that the use of fringe lenders by people on low incomes reveals important theoretical and practical insights into the relationship between the mixed economy of welfare and the mixed economy of credit in poverty survival.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.535
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.261
Teacher spread0.234 · 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