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Record W2952492911 · doi:10.5539/elt.v12n7p98

Exploring the Use of Bibliotherapy With English as a Second Language Students

2019· article· en· W2952492911 on OpenAlexvenueno aff
Eliana M. Rubio Cancino, Claudia P. Buitrago Cruz

Bibliographic record

VenueEnglish Language Teaching · 2019
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsBibliotherapyPsychologyNarrativeQualitative researchPedagogyPsychotherapistLiteratureSociology

Abstract

fetched live from OpenAlex

Studies in trauma healing and teaching ESL students have been done before. In addition, bibliotherapy has been used in educational and psychological disciplines. However, there are few studies that explore the use of bibliotherapy and trauma healing in ESL refugee students. My objective for this study was to explore bibliotherapy to see what experiences/stories surfaced from students’ lives and what connections/ reflections students made to the books we read in the bibliotherapy sessions. This was a qualitative single case study; I observed and worked with a group of ESL refugee students in an after-school program. However, for this study I followed the progress of one student over our bibliotherapy sessions. I used observations, interviews and artifacts analysis. Data was collected, triangulated and coded. I found out that the student Identified herself to some degree with the texts read during our bibliotherapy sessions. However, stories from past traumatic experiences surfaced during oral discussions but became more visible whenever she was writing.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0090.006
Scholarly communication0.0090.004
Open science0.0010.007
Research integrity0.0010.003
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 head0.044
GPT teacher head0.330
Teacher spread0.286 · 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 designObservational
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

Citations3
Published2019
Admission routes1
Has abstractyes

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