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The Future of Social Economy Leadership and Organizational Composition in Canada: Demand from Demographics, and Difference through Diversity

2016· article· fr· W2294884151 on OpenAlexvenueaboutno aff
Ushnish Sengupta

Bibliographic record

VenueInterventions économiques · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

L’article qui suit décrit les changements nécessaires et inévitables qui devraient être introduits dans la direction de l’économie sociale au Canada en raison des tendances démographiques et socioéconomiques actuelles. Les deux premières tendances sont macroéconomiques. Il s’agit, respectivement, de l’inégalité croissante des revenus et des restrictions budgétaires de longue durée aux différents paliers de gouvernement. La modification de la réalité démographique au Canada, en particulier la croissance de la population des communautés immigrantes et autochtones, est l’une des tendances socioculturelles majeures. L’économie sociale est un espace contesté et l’une des principales conclusions tirées de l’étude est que les occasions de pouvoir et de direction offerte aux groupes marginalisés et en quête d’équité, se trouvent limitées par les structures du système actuel. Les concepts de capital, d’habitus et de champ de Bourdieu servent de cadres théoriques pour montrer que les systèmes d’appui actuels au démarrage et à l’établissement d’organisations dans le champ de l’économie sociale sont conçus pour maintenir les structures de pouvoir existantes. Des structures de soutien distinctes devraient dès lors être établies.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.053
GPT teacher head0.263
Teacher spread0.210 · 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 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

Citations4
Published2016
Admission routes2
Has abstractyes

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