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
Abstract Irony is often related to humor, both in spoken and written language. One possibility is that humor arises once people reconcile the incongruity between what speakers say and imply when using irony. Humor automatically emerges in these cases given the release of tension following a momentary sense of disparity. Our claim is that this proposal does not capture many of the dynamic complexities in real-world ironic discourse. We describe psychological research on irony understanding showing that ironic meanings are not always understood via a process of drawing conversational implicatures. Studies on people's spontaneous laughter when using irony suggest that the recognition of incongruity between what is said and implied is not necessary for eliciting humor. Laughter occurs at various places in conversation, and not necessarily at the end of speakers' utterances. People also laugh for reasons other than humor, such as to signal affiliation. Overall, finding the humor in irony is not the same as seen in simple jokes, and demands examination of a complex host of contextual factors not always considered in linguistic theories of humor.
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 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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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 it