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Civil risk and landscapes of marginality in Canada: a pluralist approach to social justice

2000· article· en· W1996173077 on OpenAlexaffvenueabout
Audrey Kobayashi, Brian Ray

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsParks CanadaQueen's University
Fundersnot available
KeywordsSociologyEconomic JusticeHuman rightsContext (archaeology)Civil societyPower (physics)Gender studiesPolitical scienceLawGeographyPolitics

Abstract

fetched live from OpenAlex

The geographies of civil risk, human rights and social justice in relation to a pluralist notion of justice lie at the heart of this paper. We define civil risk as a failure of human rights, brought about by institutional processes constructed over time, space and place, which create disadvantages for marginalized social groups. Geography is integral both to civil risk and social justice because marginalization is a spatial process articulated through the deployment of institutional power across space to create socially constructed differences between dominant and subordinate groups. In this respect, we emphasize that rights are constructed in relation to dominant interests, and not according to the conditions of risk that give rise to marginalized individuals and groups. Drawing on research in social theory that emphasizes the importance of positionality and social difference, the paper argues that a principle of risk rather than rights must motivate social justice. We examine distinct forms of marginalization in Canada ‐ gender, sexual orientation, ‘race’ and aboriginal status ‐ to illustrate the importance of the historico‐geographical context of marginalization and the paradoxical nature of the relationship between risk and rights. In considering these forms of marginality and their landscapes, we argue the need for a pluralist notion of justice that will explicitly take positionality into account in achieving equality rights, reducing civil risk and mediating shared spaces. Les géographies du risque civil, des droits de la personne et de la justice sociale en relation avec une conception pluraliste de la justice sont au coeur de cet article. Nous définissons le risque civil comme un échec des droits de la personne créé par des processus institutionnels qui sont eux‐mêmes construits à travers le temps, l'espace et le lieu. Ces processus, et leur expression géographique, créent des désavantages pour les groupes marginaux dans notre société. La géographie est impliquée dans le risque civil et la justice sociale parce que la marginalisation est un processus spatial qui s'articule par le déploiement du pouvoir institutionnel à travers l'espace pour créer les différences socialement construites entre les groupes dominants et subordonnés. En ce sens, nous soutenons que les droits sont construits en relation aux intérêts dominants, mais pas en accord aux conditions de risque qui créent les individus et les groupes marginalisés. Utilisant des études en théorie sociale qui mettent un accent sur l'importance de la ‘positionnalité’ et la différence sociale, nous suggérons que le principe de risque plutôt que les droits doit motiver la justice sociale. Nous examinons quelques formes distinctes de marginalisation au Canada ‐ les rapports sociaux entre les sexes, l'orientation sexuelle, la ‘race’ et le statut autochtone ‐ pour illustrer l'importance du contexte historico‐géographique de la marginalisation et le caractère paradoxal de la relation entre le risque et les droits. En considérant ces formes de marginalité et leurs paysages, nous argumentons pour la nécessité d'avoir une notion pluraliste de justice qui considérera explicitement la ‘positionnalité’ dans tous ses efforts de réaliser les droits d'égalité, la réduction du risque civil et la médiation des espaces partagés.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0020.001
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 head0.007
GPT teacher head0.187
Teacher spread0.180 · 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 designObservational
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

Citations41
Published2000
Admission routes3
Has abstractyes

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