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Record W2609425667 · doi:10.3138/9781442679795

Set Adrift: Fishing Families

2002· book· en· W2609425667 on OpenAlexaboutno aff
Marian Binkley

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsFishingFisheryBiology

Abstract

fetched live from OpenAlex

Set against the backdrop of the fisheries crisis of the 1990s, Set Adrift examines how coastal and deep-sea fishermen's wives in rural Nova Scotia have adapted to the extraordinary pressures put on their households by the reorganization of the fishing industry. Using in-depth interviews conducted with the wives of deep-sea and coastal fishermen, members of fishermen's wives' support groups, and fish company managers, Marian Binkley explores the role of social origins and family traditions, family and social networks, and the availability of employment opportunities and social services on fishing households.Comparing and contrasting the households of deep-sea versus coastal fishers, Binkley illustrates the daily dependence of husbands upon their wives' labour and ability to adapt to often difficult and precarious living conditions. Maintaining that women make the fishing industry sustainable with their unpaid household labour, Binkley argues that the failure of Canadian government officials and policy makers to recognize the centrality of women's labour to the industry has resulted in fishers' wives bearing the brunt of the large economic and social costs generated by the current fisheries crisis. Ultimately, she contends, any analysis of production for exchange must recognize the essential contribution that household domestic labour makes to the sustainability of economic activity

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.034
GPT teacher head0.270
Teacher spread0.236 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations29
Published2002
Admission routes1
Has abstractyes

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