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Record W1497948865 · doi:10.15353/joci.v11i1.2844

Modeling Social Inclusion Systems

2015· article· en· W1497948865 on OpenAlexvenueno aff
Fábio Nauras Akhras

Bibliographic record

VenueThe Journal of Community Informatics · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityInclusion (mineral)Social sustainabilitySustainability scienceEmpowermentOntologySocial systemEngineering ethicsKnowledge managementPolitical scienceSociologyManagement sciencePublic relationsComputer scienceSocial scienceEngineeringEpistemology

Abstract

fetched live from OpenAlex

Research on sustainability science has been concerned with pointing the way towards a sustainable society. On a global scale, sustainability is seen as depending on three systems: the global system, the human system and the social system. In the social system, the need to address issues of social sustainability, including literacy, education, malnutrition, child mortality, and gender empowerment, as well as its connections with human and global sustainability, has given rise to the eight Millennium Development Goals, which break down into twenty one quantifiable targets that are measured by sixty indicators. Therefore, it is clear that the problems and issues associated with the achievement of these goals are very complex to be addressed by a single discipline and that community informatics (CI) may have an important role to play in interdisciplinary efforts to address these goals. Against this backdrop, one of the first challenges is to put the notion of a social inclusion system (a system to promote social sustainability) in more precise terms. In this direction, the purpose of this paper is to discuss and present an initial ontology to describe social inclusion systems. While ontological development in sustainability science has emphasized a problem-solution approach, we believe that the issues of social inclusion will be more naturally addressed by a situation-transformation approach, which is the focus of our ontology.

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.093
GPT teacher head0.280
Teacher spread0.187 · 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 designQualitative
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

Citations0
Published2015
Admission routes1
Has abstractyes

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