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Record W3009855980 · doi:10.1080/01419870.2020.1730927

Youth, mobilities and multicultures in the rural Anglosphere: positioning a research agenda

2020· article· en· W3009855980 on OpenAlexaboutno aff
Rose Butler

Bibliographic record

VenueEthnic and Racial Studies · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsMobilitiesScholarshipGender studiesMeritocracyLivelihoodSociologyEconomic growthEthnic groupIdentity (music)IntersectionalityPolitical scienceGeographySocial science

Abstract

fetched live from OpenAlex

Rural mobilities have transformed the social composition of rural places across the Global North. Young people are central to these changes and their role in rural livelihoods is crucial to rural futures. Yet little is known about how youth are negotiating today’s rural multicultures in an era of accelerated mobilities and on the back of decades of neoliberal restructuring. This article reviews scholarship on young people’s social relationships across ethnic and racial differences in rural Australia, the US, Canada and England, and excavates three trends within this literature. These are analyses of white and rural identity construction, policy and programme responses to rural youth “mixing”, and strategies by racialized youth to manage racisms. The paper signposts areas for prospective research at the intersection of rural studies, youth multicultures and race, and shows how this may contribute to understandings of identity and social relations for young people in the geopolitical present.

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)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.009
Scholarly communication0.0090.006
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 head0.196
GPT teacher head0.372
Teacher spread0.177 · 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 designTheoretical or conceptual
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

Citations13
Published2020
Admission routes1
Has abstractyes

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