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Record W1488147495

Paved with Good Intentions: The Failure of Passive Disability Policy in Canada

2009· article· en· W1488147495 on OpenAlexaboutno aff
Rick August

Bibliographic record

VenueeCommons (Cornell University) · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsMainstreamPovertyIncome SupportDisability benefitsEconomic growthEconomicsPublic economicsPolitical scienceDevelopment economicsBusinessSocial security
DOInot available

Abstract

fetched live from OpenAlex

It is common in the disability community to speak of unfulfilled aspirations for full citizenship and participation in the mainstream of Canadian society. In Canada, as in much of the developed world, many adults with disabilities remain outside the mainstream, especially in regard to economic opportunities. Unfortunately, many of the disability policies currently pursued by Canadian governments are unlikely to improve this situation, and may in fact make it worse. This paper offers a critical analysis of a common instrument of current disability policy, the passive cash benefit. I will focus, in particular, on the effects of passive transfers on prospects for adults with disabilities to reach their full income potential through employment. I will attempt to establish that passive income support strategies – for adults with disabilities and for low-income people in general – force their intended beneficiaries to sacrifice employment prospects for help with short-term income needs, a trade-off that reinforces poverty and dependency over the longer term.

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)0.009
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.227
Threshold uncertainty score0.897

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.028
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0320.011
Scholarly communication0.0110.003
Open science0.0050.006
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.202
Teacher spread0.187 · 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

Citations9
Published2009
Admission routes1
Has abstractyes

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