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Record W2998414872 · doi:10.3390/socsci9010003

Information Infrastructures and the Future of Ecological Citizenship in the Anthropocene

2020· article· en· W2998414872 on OpenAlexaff
Çağdaş Dedeoğlu, Cansu Ekmekcioglu

Bibliographic record

VenueSocial Sciences · 2020
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCitizenshipAnthropocentrismEnvironmental ethicsAgency (philosophy)ScholarshipSociologyPoliticsAnthropoceneSustainabilityNexus (standard)Economic JusticeConceptual frameworkEngineering ethicsEpistemologyEcologySocial sciencePolitical scienceLawBiology

Abstract

fetched live from OpenAlex

In the last two decades, the concept of ecological citizenship has become a recurrent theme in both popular and academic discussions. Discussions around the prospects of, and limitations to, ecological citizenship have mostly focused on the idea of political agency and the civic responsibility of individuals in relation to their environments, with an emphasis on environmental justice and sustainability. However, the current scholarship has yet to adequately characterize its conceptual bases and empirical applications from an information perspective. Therefore, this paper provides an overview of citizenship studies and infrastructure studies for developing more nuanced understanding(s) of epistemological models for ecological citizenship in our networked world. Drawing on the literature on information infrastructure, this paper then proposes a conceptual framework to understand ecological citizenship as constituted both discursively and techno-materially through neoliberal, anthropocentric informational infrastructures.

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 score0.490
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.295
Teacher spread0.272 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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