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Record W2105464216 · doi:10.3167/aia.2010.170103

Managing Time and Making Space: Canadian Students' Motivations for Study in Australia

2010· article· en· W2105464216 on OpenAlexaboutno aff
Heather Barnick

Bibliographic record

VenueAnthropology in Action · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationIdentity (music)NarrativeValue (mathematics)Capital (architecture)Space (punctuation)Class (philosophy)Study abroadSociologyTime spaceConnection (principal bundle)Social capitalCultural capitalPublic relationsPolitical sciencePedagogySocial scienceGeographyEngineeringEpistemologyComputer science

Abstract

fetched live from OpenAlex

This article examines the ways in which Canadian students on an exchange or study abroad programme in Australia articulated the value of their experience in connection with time and, more particularly, time constraints. Where Canadian universities often promote study abroad programmes in connection with the global knowledge-based economy, students' desires to travel abroad were more often rooted in a desire to take 'time out' while remaining productive towards the completion of future goals. Students' narratives reveal a connection between time management, travel, and the formations of a class identity. Rather than analysing time strictly as a form of capital, however, insights are generated around time as practice, that is, how time becomes an important factor in students' continual negotiations of space, social relationships, and what could be called a 'lifetime itinerary'.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.283

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0400.011
Scholarly communication0.0100.002
Open science0.0020.008
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.067
GPT teacher head0.457
Teacher spread0.389 · 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 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

Citations13
Published2010
Admission routes1
Has abstractyes

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