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Record W2759084279 · doi:10.7203/ciriec-e.90.8808

Civil society organizations and social innovation. How and to what extent are they influencing social and political change?

2017· article· en· W2759084279 on OpenAlexaff
Carolina Andion, Rubens Lima Moraes, Aghata Karoliny Ribeiro Gonsalves

Bibliographic record

VenueCIRIEC-España revista de economía pública social y cooperativa · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsConcordia University
Fundersnot available
KeywordsCivil societyPublic sphereTransformative learningPoliticsPolitical scienceSocial innovationPublic relationsPublic administrationPolitical opportunitySociologySocial movement

Abstract

fetched live from OpenAlex

This study aims to understand how civil society organizations (CSOs) perform and influence public arenas. The focus of this paper is the transformative scope of social innovation initiatives promoted by CSOsin two public arenas in Brazil: the fight against electoral corruption and the protection of children and adolescents’ rights. The research consisted of three stages: 1) controversy mapping to understand the configuration ofthese public arenas and compare the trajectories of the public problems studied; 2) observation of the “field of experience” of some CSOs that perform in these arenas; and 3) analysis of “political grammars” produced in public arenas, connecting them to the performance of the CSOs analysed. The results reveal how social innovation emerges, develops and is disseminated in the public arenas studied and highlights the similarities and differences between the two cases, discussing the practices and role of CSOs in these processes. As conclusions, the study indicates that social innovation initiatives promoted by CSOs are influenced by and have an effect on the “political culture” in the public arenas. Additionally, this work states that the regime of CSOs’ engagement in the public sphere and their performance have consequences in terms of influence on social and political changes. In the cases studied, when CSOs go beyond the logic of coproduction of public services and engage in “public inquiry” processes, their capacity to inspire social transformation seems to be enhanced.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
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 score0.794
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0080.001
Scholarly communication0.0070.003
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 head0.049
GPT teacher head0.312
Teacher spread0.263 · 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 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

Citations10
Published2017
Admission routes1
Has abstractyes

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