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Record W2979122055 · doi:10.29173/cjs29599

Re-Inscribing Gender Relations through Employment-Related Geographical Mobility: The Case of Newfoundland Youth in Resource Extraction

2019· article· en· W2979122055 on OpenAlexaffvenueabout
Nicole Gerarda Power, Moss E. Norman

Bibliographic record

VenueThe Canadian Journal of Sociology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsUniversity of British ColumbiaMemorial University of Newfoundland
Fundersnot available
KeywordsMobilitiesSociologyWorkforceAllianceGender studiesApprenticeshipResource (disambiguation)Gender relationsScholarshipEconomic growthSocial scienceGeography

Abstract

fetched live from OpenAlex

Despite the popular representation of the masculine hero migrant (Ni Laoire, 2001), rural youth scholars have found that young men are more likely to stay on in their communities, while young women tend to be more mobile, leaving for education and better employment opportunities elsewhere (Corbett, 2007b; Lowe, 2015). Taking a spatialized approach (Farrugia, Smyth & Harrison, 2014), we contribute to and extend the rural youth studies scholarship on gender, mobilities and place by considering the case of young Newfoundlanders’ geographical mobilities in relation to male-dominated resource extraction industries. We draw on findings from two SSHRC-funded research projects, the Rural Youth and Recovery project, a subcomponent of the Community-University Research for Recovery Alliance (CURRA) and the Youth, Apprenticeship and Mobility project, a subcomponent of the On the Move Partnershi We argue that the spatial coding of gender relations in rural Newfoundland makes certain kinds of mobilities more intelligible and possible for young men, while constraining women’s. In other words, gender relations of rural places are “stretched out” (Farrugia et al., 2014) across space through the mobility practices of young men and women in relation to work in skilled trades and resource extraction industries. These “stretched out” gender relations are reproduced by the organisation of a sector that relies on a mobile workforce free from care and domestic work and familiar with manual work.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.035
GPT teacher head0.252
Teacher spread0.217 · 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

Citations3
Published2019
Admission routes3
Has abstractyes

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