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Record W154583723

Farming Women's Organisations: (Re) Constructing Farm Women's Identities

2003· dissertation· en· W154583723 on OpenAlexfundaboutno aff
Deirdre Cathryn Shaw

Bibliographic record

VenueOtago University Research Archive (University of Otago) · 2003
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
FundersMinistry of Agriculture, Food and Rural AffairsDairy Farmers of OntarioOntario Ministry of Agriculture, Food and Rural AffairsOntario Fruit and Vegetable Growers' AssociationRural Women New Zealand
KeywordsAgricultureGeographyGender studiesEngineeringPolitical scienceSociologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Farm women in Western rural societies make an invaluable contribution to farming and farming communities. However this contribution is underrepresented in agri-industry. Instead farm women are predominantly associated with traditional support and service identities, such as carers and farm helpers. This thesis argues that farming women's organisations create spaces and strategic bases from which farm women may either maintain hegemonic service identities or challenge these through the performance of alternative identities. It addresses questions about the contexts in which farming women's organisations operate; the hegemonic and alternative identities farming women's organisations make available to members; the identities farm women subsequently recognise; and the way in which these identities are maintained or challenged by the collective action of the organisations.\n\nThis study explores the identities and action of farm women and their organisations, in Australia, Canada and New Zealand. It constructs an analytical framework that enables an analysis of rurality, narrative identities, organisational collectivity and political action. This framework provides the basis for a feminist methodology which incorporates multiple, and predominantly, qualitative methods. Farm women members and representatives participated in the research through organisational semi-structured interviews, questionnaires and subsequent in-depth interviews. Data were used to determine collective identity, organisational type, narrative identities, and leadership as a form of collective action.\n\nThe results indicated that farming women's organisations might be placed on a continuum based on a number of dimensions. This continuum acknowledged, but also blurred the existing binary between established organisations and newer networks. The collective identities of the organisations indicated that both the internalised and externalised constructions of collective identity are dynamic, and influence the narrative identities of farm women and their actions. Overall, members of the established organisations acknowledged and performed service identities, and undertook leadership in a feminised context, characterised by reactive communality. In contrast, members of the newer networks recognised and expressed predominately occupational identities, and undertook leadership in a masculinised context, characterised by agentic competence. Exceptions to this, however, indicated that certain established organisations and newer networks might be placed towards the middle of this continuum, indicating a need to move beyond a binary categorisation of farming women's organisations. \n\nIn sum, the thesis has demonstrated that the spaces and practices that farming women's organisations create are influential in maintaining or challenging ontological narratives which have informed dominant notions of rurality, including the hegemonic, traditional, service identities for farm women.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.233
Teacher spread0.213 · 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.

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

Citations1
Published2003
Admission routes2
Has abstractyes

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