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Enregistrement W3123654359

Changing the Norm: Positive Duties in Equal Treatment Legislation

2006· article· en· W3123654359 sur OpenAlexaboutno aff
Sandra Fredman

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueDiscrimination and Equality Law
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDiscretionPoliticsLegislationNorm (philosophy)Political scienceLaw and economicsStrengths and weaknessesContext (archaeology)BusinessPsychologySocial psychologyEconomicsLaw
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

This paper assesses the emergence of a new proactive model to achieve gender equality, and compares it with the more established complaints led model based on individual rights. While transcending many of the weaknesses of the individual complaints model, the proactive model remains ambiguous in many crucial respects, particularly as to its objectives, its use of participation, and how compliance is to be achieved. The paper aims to shed more light on these key aspects by drawing on the experiences of such models in Canada, Northern Ireland, Britain, and the EU itself. This demonstrates that the location of proactive strategies on the borderline between law and politics makes them highly dependent on political will. The key challenge is therefore to ensure that proactive strategies are based on a recognition that equality is a fundamental right, not a discretion, without reverting to individualised complaints mechanisms with all their inbuilt weaknesses. I conclude by considering how we might achieve a fundamental and non-derogable core of rights within a proactive model. Two different models are emerging for the achievement of equality: an individual complaints led model based on a traditional view of human rights; and a proactive model, aiming at institutional change. This paper aims to compare and assess these two models in the context of the EU. I argue that while the proactive model has important advantages over the more established individualised model, its weakness lies in its basis in policy rather than fundamental rights. This leaves proactive models highly dependent on political commitment and vulnerable to the vagaries of political change. The key challenge is therefore to ensure that proactive strategies are based on a recognition that equality is a fundamental right, not a discretion, and to structure the duty round the concept of a fundamental right, without reverting to individualised complaints mechanisms with all their inbuilt weaknesses. In the first part of the paper, I examine the traditional model of individual rights, highlighting its weaknesses in the context of gender equality. Part II examines the newly developing proactive model and the particular challenges it poses. This section draws on the experience of other jurisdictions to substantiate the points. I focus in particular on pay equity legislation in Canada, the race equality duty in Britain; the fair employment legislation and positive duty on public authorities in Northern Ireland; and the Open Method of Coordination in the EU as it relates to employment and social inclusion. I consider three particular aspects of the model: namely, its aims and objectives; the role of participation; and regulatory and compliance mechanisms. Part III turns to the role of each model within EU law. The first approach is found within the traditional lexicon of Treaty provisions and directives, covering both equality as such and flexibility. The second approach is found in policy documents, and soft law, and has flourished in the moist soil of the new methods of governance so popular in current EU structures. I will look particularly at gender mainstreaming and the European Employment Strategy (EES). This section highlights some of the weaknesses in these strategies, in particular the ambiguity as to aims and objectives, and the difficulties experienced in separating strategies from outcomes. I conclude by considering how we might achieve a fundamental and non-derogable core of rights within a proactive model.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,837
Score d'incertitude au seuil0,976

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,044
Tête enseignante GPT0,338
Écart entre enseignants0,293 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2006
Routes d'admission1
Résumé présentoui

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