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Record W2171546978 · doi:10.1142/s1464333206002517

BEYOND THE PILLARS: SUSTAINABILITY ASSESSMENT AS A FRAMEWORK FOR EFFECTIVE INTEGRATION OF SOCIAL, ECONOMIC AND ECOLOGICAL CONSIDERATIONS IN SIGNIFICANT DECISION-MAKING

2006· article· en· W2171546978 on OpenAlexaff
Robert Gibson

Bibliographic record

VenueJournal of Environmental Assessment Policy and Management · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsUniversity of WaterlooEnvironment and Climate Change Canada
Fundersnot available
KeywordsSustainabilityRealmGovernment (linguistics)NeglectSocial sustainabilityTriple bottom lineSustainable developmentProcess (computing)Management scienceEnvironmental resource managementPolitical scienceEcologyEconomicsPsychologyComputer science

Abstract

fetched live from OpenAlex

Sustainability is an essentially integrative concept. It seems reasonable, then, to design sustainability assessment as an essentially integrative process and framework for decision-making on undertakings that may have lasting effects. The realm of sustainability has often been depicted as the intersection of social, economic and ecological interests and initiatives. Accordingly, many approaches to sustainability oriented assessments — at the project as well as strategic level — have begun by addressing the social, economic and ecological considerations separately and have then struggled with how to integrate the separate findings. The problem is exacerbated by the generally separate training of experts in the three fields, the habitual collection of data separately under the three categories and the common division of government mandates into separate social, economic and ecological bodies. The combined effect is not merely an absence of integrative expertise, data and authority but an entrenched tendency to neglect the interdependence of these factors. The three pillars or triple bottom line approach also appears to encourage an emphasis on balancing and making trade-offs, which may often be necessary but which should always be the last resort, not the assumed task, in sustainability assessment. There are, however, important concerns underlying advocacy and application of some three pillar, limited integration approaches. Most significant are well-grounded fears that integrated, sustainability-based assessments may facilitate continued or even renewed neglect of traditionally under valued considerations, especially the protection of ecological systems and functions. This problem needs to be addressed thoughtfully in judgements about how integration is to be done. One possible solution is to take sustainability as an essentially integrative concept and to design sustainability assessment more aggressively as an integrative process. This would entail a package of regime and process design features, centred on ones that. • build sustainability assessment into a larger overall governance regime that is designed to respect interconnections among issues, objectives, actions and effects, though the full interrelated set of activities from broad agenda setting to results monitoring and response;. • design assessment processes with an iterative conception-to-resurrection agenda, aiming to maximise multiple, reinforcing net benefits through selection, design and adaptive implementation of the most desirable option for every significant strategic or project level undertaking;. • redefine the driving objectives and consequent evaluation and decision criteria to avoid the three conventional categories, to ensure attention to usually neglected sustainability requirements and to focus attention on the achievement of multiple, mutually reinforcing gains;. • establish explicit basic rules that discourage trade-offs to the extent possible while guiding the decision-making on those that are unavoidable;. • provide means of combining, specifying and complementing these generic criteria and trade-off rules with attention to case- and context-specific concerns, objectives, priorities and possibilities;. • provide integrative, sustainability-centred guidance, methods and tools to help meet the key practical demands of assessment work, including identifying key cross-cutting issues and linkages among factors, judging the significance of predicted effects, and weighing overall options and implications; and. • ensure that the decision-making process facilitates public scrutiny and encourages effective public participation.

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)0.128
metaresearch head score (Gemma)0.060
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: Empirical · Consensus signal: none
Teacher disagreement score0.128
Threshold uncertainty score0.677

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1280.060
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0070.005
Science and technology studies0.0100.115
Scholarly communication0.0400.058
Open science0.0070.025
Research integrity0.0170.035
Insufficient payload (model declined to judge)0.0060.003

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 head0.007
GPT teacher head0.332
Teacher spread0.325 · 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
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

Citations450
Published2006
Admission routes1
Has abstractyes

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