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The Farm Wife Mystery School: Women's use of social media in the contemporary North American urban homestead movement

2015· article· en· W2270622272 on OpenAlexaff
Antonia Smith

Bibliographic record

VenueStudies in the Education of Adults · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsVancouver Island University
Fundersnot available
KeywordsUrban agricultureSocial movementSociologyAgricultural educationContext (archaeology)Economic growthFood securityPolitical sciencePublic relationsPoliticsGender studiesAgricultureGeographyEconomicsLaw

Abstract

fetched live from OpenAlex

Within the larger North American food security movement, self-professed ‘urban homesteaders’ have been tearing up their backyard lawns to plant vegetable gardens and install chicken coops in search of greater self-sufficiency and independence from industrial agriculture and the corporate food chain. Participants are most often white, middle-class professionals who have no previous experience in food production or preservation and they turn to the internet and social media for support and instruction. This article considers the online community created by the urban homesteading movement as a so-called community of practice, an educational space where adult learners never meet face-to-face, but where significant informal, self-directed learning is taking place. Women's urban homesteading blogs are examined in the context of social movement learning to determine whether the use of social media as an educational and community-building tool is aiding women in furthering their food security goals. Women's gender roles in this contemporary movement are also considered, and this analysis suggests that using social media may be helping to bridge the traditional isolation expressed by previous generations of women, to reinforce a sense of political purpose to home-based food production, and to potentially create an income source for the family.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.061
GPT teacher head0.279
Teacher spread0.218 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations9
Published2015
Admission routes1
Has abstractyes

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