Language in Action: Illocutionary Acts in Anne with an E
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".