The ‘adverb-ly adjective’ construction in English: meanings, distribution and discourse functions
Bibliographic record
Abstract
We investigate a class of adjective phrases composed of a deadjectival adverb ending in -ly and an adjective head (e.g. staggeringly incompetent, absolutely terrific, fiscally responsible), a compact construction whereby two adjectives may jointly contribute to evaluative meaning. Using corpus methodologies on more than 1 million examples and relying on semantic analyses of about 1,000 instances, we propose that the construction can be divided into different semantic subtypes, including Degree (deeply disturbing), Focus (utterly ridiculous), Manner (delightfully performed), Reaction (strangely compelling), Topical (historically inaccurate) and Epistemic (intuitively obvious), among others. Using this typology, we investigate the relative distribution of each subtype across several registers of written English. We found a high frequency of the Reaction subtype in book, film and art reviews, and we suggest a discourse-functional explanation for this, linked to the perceived value of originality in expressive writing. This investigation reveals the power of semantically informed, corpus methodologies to shed light on the distribution of specific constructions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".