Placing come and go: locating the lexical item
Bibliographic record
Abstract
By examining language simultaneously along the paradigmatic and syntagmatic axes, Sinclair (2004a) identified the lexical item as an object of the discourse comprising an obligatory core and semantic prosody, and optional collocates, colligates and semantic preferences. This research investigates Sinclair’s theoretical model by locating the lexical items that are associated with the complementary verbs come and go in the spoken and written discourses in a selection of the International Corpora of English (ICE). The corpora selected are ICE-Canada, -GB, -India and –Jamaica. This research is innovative in that it adapts Sinclair’s methodology to examine high frequency lexical items across different discourses and different World Englishes It establishes that there is a significantly greater difference in frequency of the lexical items associated with come and go within the different discourses of the ICE corpora in comparison to between the ICE corpora. It replaces the core with the node, it introduces structural preference and discourse preference as co-selection components of the lexical item, and it substitutes semantic force for the term semantic prosody as defined by Sinclair: the ‘reason why [the item] is chosen’ (Sinclair 2004a: 144). Thus the lexical item comprises an obligatory node and semantic force, and optional collocates, colligates, structural preferences, semantic preferences and discourse preferences. As a consequence of these theoretical and methodological adaptations, this research shows that semantic forces with the associated co-selection components can function in tandem and that semantic forces, again with the associated co-selection components, can function in layers. The research concludes that the lexical item is not an identifiable object in the discourse, but it is the syntagmatic realisations of a paradigmatic choice.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".