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Record W2751732558 · doi:10.1186/s13012-017-0637-1

Developing a comprehensive definition of sustainability

2017· article· en· W2751732558 on OpenAlexaff
Julia E. Moore, Alekhya Mascarenhas, Julie Bain, Sharon E. Straus

Bibliographic record

VenueImplementation Science · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of TorontoCanada Research ChairsSt. Michael's Hospital
Fundersnot available
KeywordsSustainabilitySustainability scienceSustainability organizationsMedicineHealth administrationManagement scienceProcess managementEngineering ethicsPublic healthBusinessNursingEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Understanding sustainability is one of the significant implementation science challenges. One of the big challenges in researching sustainability is the lack of consistent definitions in the literature. Most implementation studies do not present a definition of sustainability, even when assessing sustainability. The aim of the current study was to systematically develop a comprehensive definition of sustainability based on definitions already used in the literature. METHODS: We searched for knowledge syntheses of sustainability and abstracted sustainability definitions from the articles identified through any relevant systematic and scoping reviews. The constructs in the abstracted sustainability definitions were mapped to an existing definition. The comprehensive definition of sustainability was revised to include emerging constructs. RESULTS: We identified four knowledge syntheses of sustainability, which identified 209 original articles. Of the 209 articles, 24 (11.5%) included a definition of sustainability. These definitions were mapped to three constructs from an existing definition, and nine new constructs emerged. We reviewed all constructs and created a revised definition: (1) after a defined period of time, (2) a program, clinical intervention, and/or implementation strategies continue to be delivered and/or (3) individual behavior change (i.e., clinician, patient) is maintained; (4) the program and individual behavior change may evolve or adapt while (5) continuing to produce benefits for individuals/systems. All 24 definitions were remapped to the comprehensive definition (percent agreement among three coders was 94%). Of the 24 definitions, 17 described the continued delivery of a program (70.8%), 17 mentioned continued outcomes (70.8%), 13 mentioned time (54.2%), 8 addressed the individual maintenance of a behavior change (33.3%), and 6 described the evolution or adaptation (25.0%). CONCLUSIONS: We drew from over 200 studies to identify 24 existing definitions of sustainability. Based on these definitions, we identified five key sustainability constructs, which can be used as the basis for future research on sustainability. Our next step is to identify sustainability frameworks and develop a meta-framework using a concept mapping approach to consolidate the factors and considerations across sustainability frameworks.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.053
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.053
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.061
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0160.012
Science and technology studies0.0040.022
Scholarly communication0.0140.025
Open science0.0030.013
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.854
GPT teacher head0.770
Teacher spread0.084 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations636
Published2017
Admission routes1
Has abstractyes

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