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Record W1988497583 · doi:10.4018/ijissc.2015010103

Interdisciplinarity in Sustainability Science

2015· article· en· W1988497583 on OpenAlexaff
Rosario Adapon Turvey

Bibliographic record

VenueInternational Journal of Information Systems and Social Change · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsLakehead University
Fundersnot available
KeywordsSustainabilitySustainability scienceEngineering ethicsDisciplinePolitical scienceContext (archaeology)GlobeSociologySustainability organizationsWork (physics)Public relationsEnvironmental ethicsSocial scienceEngineeringEcologyPsychologyGeography

Abstract

fetched live from OpenAlex

Over the last few decades, Sustainability Science (SS) has gained momentum and emerged in the academy with an extraordinary performance in knowledge production and contributions to the research and publications enterprise, growth in academic programs at the undergraduate and graduate levels, creation of centers/laboratories, and formation of scientific communities, networks and associations. Increasingly, terms like integration, collaboration and bridging of fields and disciplinary boundaries are in the forefront of conversations and/or debates. The key question addressed by this review essay is this: Is interdisciplinarity in Sustainability Science a challenge or opportunity for educational institutions and local communities in the 21st century? Considering the recent momentum in educational advancements and institutional progress, the study outlines relevant literature on interdisciplinarity in SS; synthesizes recent thinking and developments in SS and attempts to address what challenges and opportunities people across the globe face in sustainability education and research and in the development of academic programs and sustainable communities. When scientists, policy makers, academics get together as teams, partners and collaborators they are likely to be engaged in interdisciplinary work and possibly doing sustainability research, policy development and problem-solving to deal with the pressing demands and challenges of the 21st century society. In this context, it is urgent in science and society to seek solutions to major sustainability problems such as climate change and one way to address that is by doing interdisciplinary work in Sustainability Science.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.004
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 head0.068
GPT teacher head0.415
Teacher spread0.347 · 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 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

Citations6
Published2015
Admission routes1
Has abstractyes

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