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Record W2346156869 · doi:10.1111/hequ.12092

The Conditions of Movement: a Discussion of Academic Mobility between Two Early Career Scholars

2016· article· en· W2346156869 on OpenAlexaboutno aff
Bryan Gopaul, Meghan J. Pifer

Bibliographic record

VenueHigher Education Quarterly · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsArticulation (sociology)Perspective (graphical)Academic mobilitySociologyNarrativeDynamics (music)Work (physics)Movement (music)Qualitative researchCareer developmentHigher educationPedagogyPublic relationsPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Abstract Academic mobility is an increasingly crucial topic to the current and future dynamics of doctoral study and the professoriate. Much of the research has focused on US, UK and European contexts. This research explores academic mobility and the manifold issues that arise between the jurisdictions of Canada and the US, in ways that parallel and diversify previous research based on various understandings of mobility. The qualitative perspective is grounded in a reflective narrative approach that enables exploration of powerful themes. The findings indicate that there are costs, tensions and benefits to academic mobility that serve to emphasise specific personal and professional elements to the pursuit of academic life that need explicit articulation. These findings encourage additional scholarly and practical attention to the changing nature of doctoral study and of academic work and life across jurisdictions.

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)0.026
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0630.060
Scholarly communication0.0220.014
Open science0.0040.027
Research integrity0.0100.012
Insufficient payload (model declined to judge)0.0050.000

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 head0.138
GPT teacher head0.506
Teacher spread0.368 · 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.

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

Citations17
Published2016
Admission routes1
Has abstractyes

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