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Study on Pragmatic Functions of Gender Terms in Japanese Conversation

2009· article· en· W2155938649 on OpenAlexvenueno aff
Huiqing Li

Bibliographic record

VenueCanadian social science · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicGender Studies in Language
Canadian institutionsnot available
Fundersnot available
KeywordsConversationHumanitiesPhilosophyGender identitySociologyLinguisticsEthnologyGender studies

Abstract

fetched live from OpenAlex

In order to clarify the pragmatic functions of the phenomenon “Sexual Inversion” in the use of gender terms in Japanese conversation, this paper analyses respectively the pragmatic functions of the male using female terms and the female using male terms through conversational examples, presenting the point that there is compatibility between male and female terms, the use of which is not confined to gender identity of the speaker, and the flexible use of which can better express the speaker’s identity and viewpoint, moderate the talking atmosphere and coordinate relationship between the two talking sides. It is an intentional pragmatic strategy. Key words: male terms; female terms; pragmatic functions Resume: Afin de clarifier les fonctions pragmatiques du phenomene de l’inversion sexuelle dans l'utilisation des termes de genre dans la conversation en japonais, ce document analyse respectivement les fonctions pragmatiques des termes feminins utilises par les hommes et des termes masculins utilises par les femmes en nous donnant des exemples de conversation, et en presentant le point de vue qu'il y a une compatibilite entre les termes masculins et les termes feminins, dont l'utilisation ne se limite pas a l'identite sexuelle de l'orateur, et qu’une utilisation souple peut mieux exprimer l'identite et le point de vue du locuteur, moderer l'atmosphere de conversation et coordonner les relations entre les deux locuteurs. Il s'agit d'une strategie pragmatique intentionnelle. Mots-Cles: termes masculins; termes feminins; fonctions pragmatiques

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.431
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.328
Teacher spread0.291 · 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 teacher head, 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
Published2009
Admission routes1
Has abstractyes

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