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Record W1581892736

Women, Tax and Social Programs: The Gendered Impact of Funding Social Programs Through the Tax System

2000· article· en· W1581892736 on OpenAlexaffabout
Claire Young

Bibliographic record

VenueeYLS (Yale Law School) · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTax creditIndirect taxTax reformPublic economicsValue-added taxAd valorem taxSubsidyDirect taxState income taxTax avoidanceEconomicsBusinessLabour economicsMarket economy
DOInot available

Abstract

fetched live from OpenAlex

This study examines the impact on women of funding social programs through the tax system. It does so using the framework of tax expenditure analysis, which allows one to view any departure from the normative tax system (i.e., those basic rules, such as the tax rate and the tax unit, that comprise the revenue-raising part of the system) as a spending measure. The analysis also takes into account the socio-economic realities of women’s lives and concludes that many tax measures that are subsidies in respect of social programs do not benefit women to the same extent that they benefit men. Tax measures explored include the child care expense deduction, the Canada Child Tax Benefit, tax subsidies for retirement saving, the disability tax credit and tax relief for caregivers. The conclusion is that in many instances women have less access to these tax subsidies and, often, the amount they receive is less than the amount that men receive. The study concludes with a list of issues that should be considered by those involved in the tax policy process in order to ensure that women are not disadvantaged in comparison to men when tax subsidies are used to fund social programs.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.036
GPT teacher head0.294
Teacher spread0.257 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations14
Published2000
Admission routes2
Has abstractyes

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