How the position of <em>at least</em> affects its interpretation: experimental data
Bibliographic record
Abstract
The Focus-particle at least is known to be ambiguous between two interpretations: an epistemic one conveying uncertainty/ignorance, and a concessive/evaluative one that conveys a desirability ranking. Prior literature has argued that the position of at least determines what interpretation is available: at least is concessive/evaluative adsententially and epistemic adnominally. We present three experiments that investigate how three properties which the two interpretations have been taken to differ on are restricted by the syntactic position of at least, namely entailment of the prejacent, truth of higher alternatives, and desirability. The results overall support the view that the interpretation of at least is restricted by its position as previously claimed by some accounts, but syntactic position seems to dissociate the three properties in ways incompatible with previous assumptions. We discuss the implications of these results for formal accounts of at least.
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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 | 0.001 | 0.005 |
| 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 | 0.001 | 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".