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Future visioning for sustainable household practices: spaces for sustainability learning?

2011· article· en· W1953053443 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueArea · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsTrinity College
Fundersnot available
KeywordsSustainabilitySustainable consumptionCitizen journalismConsumption (sociology)IncrementalismCorporate governanceProduction (economics)AssertionSociologyEconomicsPolitical scienceSocial scienceManagementComputer scienceLaw

Abstract

fetched live from OpenAlex

Despite widely articulated concerns about unsustainable production and consumption processes, governance interventions have led to only incremental shifts in routinised production and consumption behaviour, particularly within households of western, industrialised societies. In response, techniques of future visioning have been mooted as more ambitious governing mechanisms that could help to liberate policymakers and other stakeholders from current patterns of disjointed incrementalism in the field of sustainable production and consumption. At the heart of these claims is the assertion that visioning promotes learning that can lead to the emergence of innovative approaches to sustainability challenges from problem redefinition to practical action. This paper examines the extent to which participatory visioning creates spaces for sustainable learning using empirical evidence from workshops focused on transforming household consumption practices in Ireland. It is concluded that participatory visioning approaches do provide supportive physical places and intellectual spaces for personal and collaborative learning with regard to potential sustainability transformations. The bounded nature of the particular workshops examined, in terms of duration, focus and participants, means that embedding such learning within wider organisational structures and practices is likely to be a much less certain process that, if it does occur, will unfold over longer timescales and in unpredictable ways.

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.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.276
Teacher spread0.249 · 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