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Record W3006131634 · doi:10.4324/9780429293429

TESOL and the Cult of Speed in the Age of Neoliberal Mobility

2020· book· en· W3006131634 on OpenAlexaboutno aff
Osman Z. Barnawi

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
Fundersnot available
KeywordsCultSociologyPolitical scienceHistoryAncient history

Abstract

fetched live from OpenAlex

TESOL and the Cult of Speed in the Age of Neoliberal Mobility argues that because the nexus between TESOL and the cult of speed in an age of increased neoliberal mobility has not yet been explicitly unpacked, discussed, identified and theorized, the implications of this socio-economic phenomenon for TESOL policies, curricula, pedagogies and practices have been overlooked. Through the presentation of several qualitative case studies, the book illustrates the social dynamics of speed and its key aspects (i.e., the materiality and the politics of time) in different TESOL contexts, including Saudi Arabia, the USA and Canada. The aim in presenting these diverse case studies was to craft a collection of responses, which, when put together, could offer new insights into the TESOL academic community. The book examines the ways in which the cult of speed has been envisioned, celebrated, negotiated with, enacted and justified by the various actors within the contemporary field of TESOL. It also investigates the new language teaching practices and forms the cult of speed in TESOL has generated and is generating. TESOL and the Cult of Speed in the Age of Neoliberal Mobility will be of interest to TESOL/applied linguistics educators, students, policy makers, administrators, employers and the wider community, and it is hoped will give them ideas about how to deal with today’s culture of fast movement in the globalized higher education landscape.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.666
Threshold uncertainty score0.982

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 studies0.0000.001
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 head0.031
GPT teacher head0.297
Teacher spread0.266 · 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 designTheoretical or conceptual
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

Citations17
Published2020
Admission routes1
Has abstractyes

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