Connectionism, HPSG signs and SLA representations: specifying principles of mapping between form and function
Bibliographic record
Abstract
A current limitation of the connectionist approach to second language acquisition (SLA) research is that it does not, to my knowledge, include complex linguistic representations. This article proposes a partial solution to this limitation by motivating and illustrating specific analyses that utilize the sign-based representations developed within Head-driven Phrase Structure Grammar (HPSG). To motivate the proposed representations, the article applies them to an analysis of four types of mappings between form and function: one-to-one, primed redundancy, nonprimed redundancy and polyfunctional. The paper summarizes representative SLA data that indicate how these mappings may appear in second language (L2) production. Key properties of HPSG analyses are discussed, indicating how they are consistent with connectionist assumptions. Sign-based representations of the four types of mappings are then provided, including several modifications to HPSG formalisms. The article concludes with a discussion of future directions.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".