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Record W7113354761

Working with verbal and multimodal forms in identity texts in the framework of SFI-course

2023· article· sv· W7113354761 on OpenAlexaboutno aff

Bibliographic record

VenueDalarna University College Electronic Archive · 2023
Typearticle
Languagesv
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)MultilingualismMultimodalityLanguage acquisitionDiscourse analysisNeuroscience of multilingualism
DOInot available

Abstract

fetched live from OpenAlex

In the framework of second language learning, developed in Canada in the early 2000s, identity texts were a part of a bilingual or multilingual artefacts where students produced many variants. They presented texts as written, spoken, signed,visual, musical, dramatic or multimodal forms. As a result of students’ investment in their own identities, identity texts were considered as a meaningful way to validate multilingualism by inviting students to bring their home languages into the classroom. This thesis aims to investigate the use of verbal and multimodal forms while working with identity texts in a course of Swedish for immigrants, during a monthlong project “New beginning in Sweden”, which took place in a school in the centralof Sweden. Furthermore, this thesis aims to provide students' points of view on the whole process. Combining the method of semi-structured interviews along with observational research in the Swedish for immigrants’ classroom which has identit texts in focus, the thesis tries to answer the following questions:• How was the work with both verbal and multimodal forms of identity texts carried out with the students?• What do students think about working with multimodal forms of identity texts as the second phase of working with verbal texts?• How do students feel that different ways of working with identity texts contributed to their learning of Swedish as a second language? Results of the thesis show that the whole project would have given even better outcome if students were given more time while working with multimodal identity texts. Furthermore, which the students mentioned, they would have liked to have had more freedom in the creativity process, although they do not consider working with identity texts as empowering for their language skills. On the other hand, they describe it as an interesting pause from regular lessons. Last but not least, students were not in favour of working with verbal forms of identity texts because they were not used to be allowed to use their first language while learning their second language. This might complicate their upcoming learning process.

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)0.005
metaresearch head score (Gemma)0.007
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 score0.011
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0090.016
Scholarly communication0.0110.005
Open science0.0010.008
Research integrity0.0010.002
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 head0.018
GPT teacher head0.325
Teacher spread0.308 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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