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Record W3147853145 · doi:10.1080/15487733.2021.1902062

Challenging practices: experiences from community and individual living lab approaches

2021· article· en· W3147853145 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

VenueSustainability Science Practice and Policy · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsUniversité Laval
FundersEuropean Commission
KeywordsLaundryAssisted livingSustainabilityPublic relationsLiving labFocus groupCommunity engagementSociologyPsychologyEveryday lifeSocial psychologyMarketingPolitical scienceBusinessComputer scienceEcology

Abstract

fetched live from OpenAlex

In this article, we examine a change initiative designed to involve households in testing ways to transform two everyday practices ‒ heating and doing laundry. The research design included an examination of the challenges of changing practices either in a setting that fosters collective engagement or with individual households. Two different types of living labs were carried out simultaneously in eight European countries in Autumn–Winter 2018. We reflect on differences in results in terms of both changes in practices and the experiences of participating households that we argue can be at least partially attributed to householders’ engagement in different types of living labs. We discuss the implications of an individual-focused vs. community-oriented approach for change initiatives seeking to challenge social norms for sustainability transitions, concentrating in particular on differences in the nature of participants’ engagement and their willingness and ability to challenge routine practices. This is complemented by analytical reflections on the differences in design, interaction, and performance between the two types of living labs. We show that an explicit focus on collaborative engagement in living labs can produce results that reflect shared experiences, community support, challenging established norms, and collective commitment toward change.

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)0.006
metaresearch head score (Gemma)0.048
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.002
Scholarly communication0.0010.006
Open science0.0000.002
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 head0.087
GPT teacher head0.333
Teacher spread0.246 · 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