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Record W2790778498

Financial accessibility and inclusive value systems for finance, tax and accounting practices: Advocacy and design recommendations for accessible practices and disability tax rights.

2015· other· en· W2790778498 on OpenAlexaboutno aff
C N Brooke

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2015
Typeother
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsDisadvantagedPopulationPublic economicsBusinessOrder (exchange)Tax reformFinanceEconomicsEconomic growthMedicine
DOInot available

Abstract

fetched live from OpenAlex

There is a proportionally significant marginalized aging and disabled population in Canada from perspectives of equitable financial means and access. While in recent years there has been increased effort from the federal and provincial governments through the Income Tax Act of ongoing incremental tax provisions and adjustments in order to integrate and provide equal opportunity to people with disabilities, these efforts do not reflect a comprehensive and coordinated approach, or a coherent disability tax strategy. Issues such as the cost outlay of disabilities (medication, support, and treatments), access and stability in the labor force, caregiver and family support, retraining and higher education and general income support are all outstanding issues in need of much reform [20]. It is therefore necessary to persist in efforts to make positive change and actively build on prior political successes to continue to push for tax policy reform to promote equal access and integration within the broader society. This report investigates design strategies and opportunities for influencing dialogue between the federal departments and agencies, advocacy groups and the disadvantaged general public, based on a deep understanding of the impact of disabilities on families, the disability tax provisions and existing support mechanisms in order to arrive at meaningful recommendations to reduce social gaps and to reduce economic inequality.

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)0.025
metaresearch head score (Gemma)0.037
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: Other
Teacher disagreement score0.225
Threshold uncertainty score0.448

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.037
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0080.011
Scholarly communication0.0150.009
Open science0.0040.008
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0150.002

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 head0.231
GPT teacher head0.464
Teacher spread0.233 · 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
Published2015
Admission routes1
Has abstractyes

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