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Record W3088029007 · doi:10.1111/spol.12655

Determinants of social assistance caseloads for employable single adults without dependants in Canada

2020· article· en· W3088029007 on OpenAlex
Nick Falvo, Ali Jadidzadeh

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

VenueSocial Policy and Administration · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsUniversity of CalgaryCarleton University
Fundersnot available
KeywordsTreasurySocial assistanceGovernment (linguistics)JurisdictionSocial securityBusinessValue (mathematics)Demographic economicsEconomic growthEconomicsPolitical scienceLabour economicsMarket economyLaw

Abstract

fetched live from OpenAlex

Abstract Government officials like the idea of just a small number of households in their respective jurisdiction receiving social assistance. A large number is seen as costly to the public treasury, and declining caseloads are generally viewed as a mark of success for both the economy and the government of the day. But what factors account for the size of a Canadian province's social assistance caseload? This article aims to shed light on this question, with a focus on single adults without dependants (and without serious disabilities) during the 1989–2017 period. One important finding is that when the value of social assistance benefit levels for this group increases by 1% in a province, the social assistance caseload for this demographic rises by 0.457%. Put differently, there is indeed an important behavior response associated with higher benefit levels. In response, we propose that provincial officials budget for higher take up levels when they increase benefit levels for this household group.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.076
GPT teacher head0.441
Teacher spread0.365 · 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