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Record W7163842345

A Case Study of a Japanese Child: Language Development through Immersion in a Summer Camp

2002· article· en· W7163842345 on OpenAlexaboutno aff
Madoka Kawano

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsForeign languageSummer campVocabularySummer vacationWorryFirst languageImmigrationPeriod (music)
DOInot available

Abstract

fetched live from OpenAlex

IntroductionWith an ever increasing emphasis on globalization, acquiring English language skills has become a vital issue not only in Japan, but also around the world.Among the various options now being considered to aid in the acquisition of English or of any foreign language, intensive exposure to the target language has proven to be one of the most effective methods.Regardless of the length of time spent in such programs, immersion in the target Ianguage benefits a learner in numerous ways.With regards to children, it is commonly accepted that they adapt to new environments and different languages in a relatively short period of time.Home stays, student exchange programs, as well as various summer camp programs in foreign countries, especially in the States, Canada, and Great Britain accept students with various backgrounds from all over the world.These countries do have a tradition of hosting foreign students and providing different activities for them, depending on individual needs.For Japanese children wanting to participate in such a program, summer camp, especially sleep-away camp is an ideal choice for many reasons; camps provide a secure and safe environment away from big cities.Children attending summer camps in English speaking countries are exposed to English 24 hours a day.In this type of relaxed setting, children feel very little pressure, since they do not have to worry about academic success and they are together with other children of the same age.Children seem to tmagically pick up' new vocabulary throughout the entire day through routine activities like at meal time, as well as through

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0090.004
Scholarly communication0.0020.002
Open science0.0020.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.059
GPT teacher head0.280
Teacher spread0.221 · 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 designCase report
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
Published2002
Admission routes1
Has abstractyes

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