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Record W3044096646 · doi:10.17507/tpls.1008.07

Research on Culture Shock of International Chinese Students from Nanjing Forest Police College

2020· article· en· W3044096646 on OpenAlexaboutno aff
Li Shen, Jie Chen

Bibliographic record

VenueTheory and Practice in Language Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCentral Asia Education and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsShock (circulatory)Research ObjectPolitical scienceChinese culturePublic relationsPsychologyChinaBusinessLawMedicineBusiness administration

Abstract

fetched live from OpenAlex

At present, many domestic police colleges are constantly promoting foreign exchanges and cooperation. They have established extensive inter-school cooperation with foreign police education and training institutions and police colleges. More and more Chinese students of police colleges go abroad to judicial institutions and police colleges of various countries for short-term study or visit. Due to cross-cultural differences and other factors, these international Chinese students often encounter culture shock at English-speaking countries. This article takes eleven students from Nanjing Forest Police College (NFPC) as the survey object, conducts dynamic research applying interviews and questionnaires, explores the culture shock they experienced in six-month life and learning in 2019 in Canada, analyzes the internal and external causes, and proposes the countermeasures to cross-cultural adaption for international Chinese students in police colleges.

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)0.002
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 score0.096
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.066
GPT teacher head0.512
Teacher spread0.446 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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