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Record W4389453251 · doi:10.3390/su152416647

Exploring the Impact of the Sustainable Development Goals on Sustainability Trends

2023· article· en· W4389453251 on OpenAlexaff
Eduardo Ordonez‐Ponce

Bibliographic record

VenueSustainability · 2023
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsAthabasca University
Fundersnot available
KeywordsSustainabilitySustainable developmentSustainability organizationsSustainability scienceEnvironmental economicsBusinessSocial sustainabilityEnvironmental resource managementEnvironmental planningPolitical scienceEconomicsGeography

Abstract

fetched live from OpenAlex

The SDGs have made a significant contribution to the sustainability movement, being used by many organisations from across sectors all over the world as their sustainability framework. However, have they impacted the previous trend of sustainability challenges just because of their existence? This article aims to contribute to answering this question by statistically comparing the trends in the sustainability performance of the SDGs before and after they were launched in 2015. Data were collected for every SDG and their trends were quantitatively assessed using non-parametric tests, finding that most of the SDGs have not significantly improved and that most of the sustainability indicators are still performing poorly in developing countries. While this research is exploratory and does not assess the direct impact of the SDGs on sustainability, it suggests that for the most part, the SDGs have not significantly changed sustainability trends since they were launched in 2015, which is a concerning finding. This article should serve as a wake-up call to design more suitable sustainability frameworks as the SDGs expire in 2030, and for those using them to be more critical of their reach rather than being satisfied with a framework that although helping will not achieve its main goal.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.035
GPT teacher head0.294
Teacher spread0.258 · 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 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

Citations34
Published2023
Admission routes1
Has abstractyes

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