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Income Support for Persons With Disabilities

2017· article· en· W6959912233 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPasture and Agricultural Systems
Canadian institutionsnot available
Fundersnot available
KeywordsCrunchGovernment (linguistics)PaymentIncome SupportInflation (cosmology)Value (mathematics)Index (typography)

Abstract

fetched live from OpenAlex

Alberta, British Columbia and Ontario all maintain separate income-support programs for the disabled. This paper examines the criteria applicants must meet for each program and traces variations in monthly payment levels in relation to political exigencies and inflationary pressures affecting the cost of living. As it is impossible to settle on a definitive way to measure poverty, the authors present several proposals and compare all of them with the income recipients realize from each of the three programs. While acknowledging that the precise level of income support for the disabled is ultimately a value judgment, they suggest that the existing income-support program provided by the federal government for impoverished seniors is a suitable baseline. The authors crunch the numbers to reveal the amounts Alberta, BC and Ontario would have to spend to bring their existing income-support programs for the disabled up to the level of similar programs for seniors. Finally, they recommend that governments index income support for the disabled to inflation. Governments already take inflation into account for taxpayers and seniors and the authors believe the disabled should not be treated differently.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.458
Threshold uncertainty score0.912

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.001

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 head0.018
GPT teacher head0.193
Teacher spread0.175 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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