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Record W2046001593 · doi:10.1108/02610150710756658

Organising for voting rights of people with disabilities in Lebanon: reflections for activists

2007· article· en· W2046001593 on OpenAlexaff
Samantha Wehbi, Yahya El‐Lahib

Bibliographic record

VenueEqual Opportunities International · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsGrassrootsContext (archaeology)Value (mathematics)VotingPolitical sciencePublic relationsSociologyOriginalityPoliticsGovernment (linguistics)Diversity (politics)Public administrationSocial scienceLawQualitative research

Abstract

fetched live from OpenAlex

Purpose Through a reflection on a recent voting rights campaign for people with disabilities in Lebanon, the article aims to contribute to a body of literature that seeks to challenge the marginalisation of people with disabilities; and aims to share our reflections with others interested in deeper thinking on the global impacts on their day‐to‐day work. Design/methodology/approach The article begins with a background discussion of the Lebanese context and the voting rights campaign, followed by an analysis of rights‐based work through a discussion of key issues faced by community activists. Findings The analysis highlights the impact of global forces on local grassroots work through the following issues: formalisation of relationships between national government organisations (NGOs); professionalisation within NGOs; contentious dealings with the state; the meanings and uses of diversity and international political relations. Originality/value There is a dearth of published studies on the disability‐rights movement in the Arab region; more specifically, the article provides a critical reflection on the changes facing the movement in Lebanon, where there are no published studies on the topic. This article would be of value to activists in other parts of the world interested in the changes facing activism on disability rights or other issues.

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 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 score0.655
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.151
GPT teacher head0.425
Teacher spread0.274 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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