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Record W4280524471 · doi:10.1007/s44168-022-00009-2

What does neighbourhood climate action look like? A scoping literature review

2022· article· en· W4280524471 on OpenAlex
Neelakshi Joshi, Sandeep Agrawal, Shirley Lie

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueClimate Action · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsUniversity of Alberta
FundersAlberta Ecotrust Foundation
KeywordsNeighbourhood (mathematics)Framing (construction)Climate changePublic relationsSustainabilityPolitical scienceEnvironmental planningGeographySociologyEcology

Abstract

fetched live from OpenAlex

Abstract Cities are recognized as an important scale for framing and implementing plans and policies for action on climate change. Within the structure of cities, it is in urban neighbourhoods that climate action becomes tangible and has the potential to engage communities. Despite its importance, scholarly literature has played limited attention to the scale of the neighbourhood as a site for locating climate action. The objective of our paper is to provide an overview of the role of neighbourhoods in leading bottom-up climate action and its implications for urban planning based on a qualitative scoping review. Our findings indicate that neighbourhoods are conceptualized as a physically bounded scale for climate action as well as a web of social networks and relationships enabling this action. Neighbourhood climate action aims to achieve neighbourhood scale sustainability and resilience by engaging with residents, municipalities, local academic institutions, neighbourhood associations and non-governmental agencies. Scholars engage with a wide range of concepts like place-based attachment and social mobilization as well as established practice-oriented tools in defining and measuring neighbourhood climate action. However, the neighbourhood scale struggles with limited resources and power in creating sustained climate action as well as in engaging with and addressing socio-economically marginalized communities.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.639
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0010.004
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 head0.107
GPT teacher head0.375
Teacher spread0.268 · 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