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Record W4385216775 · doi:10.4324/9781003447115-15

Between the Worlds

2023· book-chapter· en· W4385216775 on OpenAlexaboutno aff
Yan Guo

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsGeology

Abstract

fetched live from OpenAlex

The author helps himself regain confidence in second language writing. He explores his autobiographical self by reflecting on his personal experience of learning to write in English. The author examines the process of how he, as a successful and confident writer in China, became an incompetent writer at the beginning of graduate school in Canada, of how he struggled to “appropriate voices”, and eventually regained his confidence in English. He explores and positions himself, a nonnative Teaching English as a Second Language professional in an English-speaking environment. He describes how he struggled to create a hybrid identity in the process of learning to write in his second language. This process is guided by an underlying assumption that language can be seen as an act of identity and writing as giving voice to that identity. He takes an antiessentialist view of identity, identity is not a fixed personality trait that is independent of the social context, but is socially constructed.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.040
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.014
Scholarly communication0.0180.015
Open science0.0010.011
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0400.013

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 head0.105
GPT teacher head0.254
Teacher spread0.149 · 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 designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

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