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Record W1569409518

Summary Of: Social Assistance Use in Canada: National and Provincial Trends in Incidence, Entry and Exit

2005· article· en· W1569409518 on OpenAlexaboutno aff
Ian Irvine, Ross Finnie, Roger Sceviour

Bibliographic record

VenueAnalytical Studies Branch Research Paper Series · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDisadvantageRecessionContext (archaeology)WorryMainstreamDependency ratioDemographic economicsPolitical scienceEconomic growthEconomicsGeographyDemographyPsychologySociologyPopulation
DOInot available

Abstract

fetched live from OpenAlex

This paper summarizes findings from the research paper entitled Social Assistance Use in Canada: National and Provincial Trends in Incidence, Entry and Exit. For many Canadian families, Social Assistance (SA) usage reflects near-destitution and an exclusion from the social and economic mainstream. For children, it can represent a critical period of disadvantage with potentially lasting effects. While committed to SA, governments worry about cost. Thus, when SA participation rose during the recession of the early 1990s, virtually all provinces instituted changes to reduce SA dependency. Eligibility rules were made tighter, benefit levels cut, and 'snitch' lines introduced. Following these changes, and the economic recovery post-1995, the number of SA-dependent individuals dropped from 3.1 million to under 2 million by 2000, while benefits received fell from $14.3b in 1994 to $10.4b in 2001 (current dollars). This paper maps the cycle of SA dependency, focusing on empirical records of SA entry, exit, and annual participation rates, placing these in the economic and policy context of the 1990s. The paper begins with a description of the database used, sample selection and editing procedures, the unit of analysis, a definition of SA participation, and the measure of entry and exit from SA. It then turns to the economic and policy backdrop of the 1990s, before showing results at the national and provincial levels. We conclude with a summary of main findings.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.972
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.017
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.003

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 head0.083
GPT teacher head0.389
Teacher spread0.306 · 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 designObservational
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

Citations4
Published2005
Admission routes1
Has abstractyes

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Same venueAnalytical Studies Branch Research Paper SeriesSame topicCanadian Policy and GovernanceFrench-language works237,207