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Record W2982031223 · doi:10.1075/ip.00036.kim

Agency and impoliteness in Korean online interactions

2019· article· en· W2982031223 on OpenAlex
Ariel Kim, Lucien Brown

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternet Pragmatics · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHonorificPolitenessAgency (philosophy)DiscernmentFocus (optics)PsychologyCustomer careSocial psychologyLinguisticsSocial mediaPublic relationsSociologyComputer scienceBusinessPolitical scienceMarketingWorld Wide WebEpistemology

Abstract

fetched live from OpenAlex

Abstract (Im)politeness research has often focused either on the importance of social norms or on the intentions of the speaker, with the active role of the listener in assigning social meanings overlooked. This limitation particularly applies to so-called “discernment languages” such as Korean and Japanese. The current paper addresses this gap by offering a small-scale qualitative study of recipient agency in Korean naturally occurring computer-mediated communication (CMC). The data analyzed includes 14 text messages between the recipient (the proprietor of an online food business) and his customer, which were posted on a blog that he owned and operated. We focus on how the recipient agentively evaluates the language usage of the customer, including inconsistent evaluations of her use of non-honorific language, or panmal . The results suggest that the instability of (im)politeness interpretations cannot be explained solely by social norms or intentions but should also include the socially-mediated agency of the recipient.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.739
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.304
Teacher spread0.268 · 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