Bibliographic record
Abstract
This chapter describes the main themes of the volume, including “the scope of irony” (the diverse ways that irony is manifested in human experience), “irony’s impact” (e.g., the complex ways irony affects both personal and social life), “irony in linguistic communication,” “irony, affect, and related figures,” and “irony in expressive, multimodal contexts.” Taking a close look at chapters from different sections of the volume illustrates some of the incredibly diverse ways of studying, and writing, about irony in human life. We urge readers to pay close attention to the examples discussed, methods employed by different scholars, the way their arguments unfold, and their larger aims to address the ways irony and thought are closely intertwined. And we should remain open to being “shaken up” by what is read for the wide world of irony scholarship can disrupt our preconceived notions about the meaning and functions of irony exactly in the ways that irony itself can “piece illusions” about how we see ourselves, each other, and the world around us.
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 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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".