A multivariate analysis of the Old English ACC+DAT double object alternation
Bibliographic record
Abstract
Abstract In Old English, the ditransitive construction with an accusative (direct) object and a dative (indirect) object occurred with two alternating object orders: ACC-DAT vs. DAT-ACC. This study examines the motivations behind the OE speakers’ choice for one of both orders. The effect of 16 factors was evaluated based on a corpus sample of N = 2409 sentences drawn from the York-Toronto-Helsinki Parsed Corpus of Old English Prose (Taylor et al. 2003). The data was analysed by means of a mixed-effects logistic regression analysis. The results indicate that the ACC+DAT alternation was largely driven by the same factors that motivate the dative alternation in later stages of British English. However, no evidence was found for specific verb preferences in Old English, which suggests that the OE object alternation was less driven by semantics than the dative alternation in PDE. It is argued that the results further substantiate Wolk et al.’s (2012) claim that the cognitive mechanisms underlying present-day probabilistic patterns also underlie past variation.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".