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Record W2511852241 · doi:10.1080/01490400.2016.1216812

An Ecofeminist Narrative of Urban Nature Connection

2016· article· en· W2511852241 on OpenAlexaffabout
Bryan S. R. Grimwood

Bibliographic record

VenueLeisure Sciences · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Philosophy and Ethics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNarrativeStatus quoSociologyCritical consciousnessEcofeminismResistance (ecology)Power (physics)PoliticsAestheticsSense of placeEnvironmental ethicsGender studiesSocial sciencePolitical scienceEcologyPedagogyLaw

Abstract

fetched live from OpenAlex

The purpose of this study was to explore meanings, experiences, and perceived impacts associated with an urban nature connection program as narrated by mothers of program participants. “Project Connect”, a charity organization established in 2008, delivers the program investigated in urban parks and green spaces in Toronto, Canada. Drawing on ecofeminism and narrative inquiry, the study reveals a community narrative that depicts how Project Connect serves a group of mothers as an incubator of relationships spanning social and environmental domains, and which enable resistance of status quo forces that shape contemporary cityscapes. Nature connection in this sense is very much a political and cultural process that opens opportunities to challenge but also reproduce aspects of the dominant nature-related discourses. Accordingly, this study prompts consideration of the power of mothers and an ethics of care to transform human-nature relationships, and weaves critical consciousness and cautious re-valuing around the nature narratives we tell.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.017
Scholarly communication0.0040.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.271
Teacher spread0.257 · 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 designQualitative
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

Citations17
Published2016
Admission routes2
Has abstractyes

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