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Record W2122440673 · doi:10.1111/glob.12017

Memoir/manuals of South Korean pre‐college study abroad: defending mothers and humanizing children

2013· article· en· W2122440673 on OpenAlexfundno aff
Nancy Abelmann, Jiyeon Kang

Bibliographic record

VenueGlobal Networks · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
FundersUniversity of British ColumbiaUniversiteit LeidenAcademy of Korean StudiesUniversity of Virginia
KeywordsMemoirGooseDocumentationSociologyGender studiesPsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract In this article, we analyse the memoir/manuals of three ‘goose’ families. These are South Koreans whose children participate in pre‐college study abroad (PSA). One parent (typically the mother) accompanies the child while the other (usually the father) remains at home to support the venture. Although many South Koreans aspire to study abroad, both the mothers and children of goose families have attracted wide criticism – the mothers for being narrowly instrumental and too family centred, worried only about social reproduction and mobility and the children for forsaking their nation, foregoing their filial duties and, perhaps, failing abroad. These memoir/manuals defend the goose mother and protect the PSA child against such charges. As memoirs, they depict remarkable people worthy of documentation. As manuals, they offer (at least some) guidance for mothers and families contemplating this particular family strategy. The memoir/manuals open a window to the challenges and anxieties of PSA in South Korea today.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.009
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.011
Scholarly communication0.0030.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.014
GPT teacher head0.280
Teacher spread0.266 · 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

Citations40
Published2013
Admission routes1
Has abstractyes

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