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Record W4389992491 · doi:10.7202/1108104ar

Older people, discrimination and citizenship: What specific insights in light of disability law on the national and international level?

2023· article· en· W4389992491 on OpenAlexvenueno aff
Marie Mercat‐Bruns, Tatiana Gründler

Bibliographic record

VenueAequitas Revue de développement humain handicap et changement social · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDiscrimination and Equality Law
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipConventionConvention on the Rights of Persons with DisabilitiesScope (computer science)International lawHuman rightsPolitical scienceDemocracyLawPsychologySociologyLaw and economicsPoliticsComputer science

Abstract

fetched live from OpenAlex

Our research first delves into the complexity of ageism in law to understand to what extent the existing legal norms are sufficient to encounter the stereotypes linked to old age and the individual as well as systemic discrimination which ensues. According to European and national case law, age is an ambiguous ground of discrimination law and masks the complexity of age discrimination. It seems the scope of the UN Convention on the Rights of People with disabilities overlaps with some difficulties of older people in terms of rights but the CRPD also illustrates how an international convention can be a game changer, creating an impetus to gain insight on the particular characteristics of disability, but not age. The concept of disability discrimination has in turn enriched the way we think of discrimination in a more relational way. In order to prove the inadequacies of the current international legal framework on the human rights of older people, the second part of our study will illustrate how the right to vote exemplifies the challenges of age discrimination in terms of citizenship and full participation of older people in the democratic process, demonstrating the need to adopt a tailored international convention for older individuals.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.557
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.194
GPT teacher head0.403
Teacher spread0.209 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAequitas Revue de développement humain handicap et changement socialSame topicDiscrimination and Equality LawFrench-language works237,207