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Record W4407232557 · doi:10.30564/fls.v7i2.8309

Language in Action: Illocutionary Acts in Anne with an E

2025· article· en· W4407232557 on OpenAlexaboutno aff
Thaweesak Chanpradit, Juthamanee Noreesuwan, Rawicha Thiwarangsan, Naruenat Saifa

Bibliographic record

VenueForum for Linguistic Studies · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsnot available
FundersKasetsart University
KeywordsAction (physics)LinguisticsCommunicationSociologyPsychologyCognitive sciencePhilosophyPhysics

Abstract

fetched live from OpenAlex

Illocutionary acts are speech acts in which the speaker encodes an intended meaning in an utterance, and the listener decodes this meaning from the utterance. Illocutionary acts are not based on form (grammar) but rather on meaning. This study examines illocutionary acts used by the characters in the first season of the Canadian period drama television series Anne with an E, presented by Netflix. The subtitles presented by the series were analyzed using a Searle approach. Contextual cues that shed light on the nuances of the utterances and expressions of the characters were noted. The results of the study indicated the presence of all five primary classifications of illocutionary acts within the series. These illocutionary acts were ranked from the most to the least prevalent, beginning with assertives, accounting for a substantial 40.72% of the total dataset, followed by directives, constituting 30.13%. Commissives were observed to be 7.26% of the instances, while expressives made up 21.14% of the dataset. Finally, declaratives were the least frequently utilized, representing a mere 0.86% of the total data. Thus, language serves not only to convey straightforward sentences but is also used to express both actions and interactions.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.873
Threshold uncertainty score0.992

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)0.0000.000

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 head0.049
GPT teacher head0.339
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 designTheoretical or conceptual
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

Citations1
Published2025
Admission routes1
Has abstractyes

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