The Accusative Plus Infinitive Construction in English
Bibliographic record
Abstract
Abstract This chapter focuses on the English accusative plus infinitive (A + I) construction, which in the generative literature is known as the raising to object construction and the exceptional case‐marking construction. The A + I construction is an examplepar excellenceof a syntax–semantics mismatch and so has played a central role in our understanding of grammatical relations, semantic relations, and the ways in which syntax coordinates both of these. This chapter discusses what we call the two major “brands” of analysis: raising to object and exceptional case‐marking. We provide an overview of the evidence that has accumulated both for and against each of the brands over the decades. Further, we discuss more recent analyses that countenance the possibility that both brands may coexist. We review more recent research that investigates cases where A + I is interestingly blocked, a topic with renewed interest in the last decade. Finally, we discuss semantic issues associated with A + I and facts that challenge the assumption that A + I and related finite clauses are synonymous.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".