‘What the X’ in Anglophone government meetings: Areal distribution, emotionality, and euphemism
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.
Bibliographic record
Abstract
• Offensive expressions vary by region in English-speaking government meetings. • Euphemisms vs. “what the hell” differ in emotional intensity and acceptability. • emotion2vec reveals anger levels in speech across English-speaking countries. This article examines the use of potentially offensive expressions, specifically “what the hell” and its euphemistic variants, in local government meetings across English-speaking countries. Two primary research questions are addressed: first, are there noticeable differences in the frequency of these expressions between countries and within regions? And second, how do euphemistic alternatives compare to “what the hell” in terms of emotional intensity and valence, both across and within national varieties? The study draws on data from three large, recent corpora of geolocated automatic speech recognition (ASR) transcripts and the corresponding underlying audio to explore the geographic distribution and emotional nuances of these expressions in various English-speaking countries, including the US, Canada, the UK, Ireland, Australia, and New Zealand. To assess the emotionality of expressions, specifically anger, the speech emotion recognition model emotion2vec is employed. The findings provide insight into how the acceptability and emotional weight of “what the hell” and variants differ across regions. Additionally, the study demonstrates the potential of vector-based representations of speech in multimodal corpus analysis, while empirically validating theoretical claims in semantics related to pejoration and euphemism.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it