The use of -<i>ing</i> and -<i>ndo</i> forms in sales contracts
Bibliographic record
Abstract
Abstract This paper analyzes the use of the -ing and -ndo forms in English and Spanish in sales contracts. More specifically, it aims to answer three questions: 1. Do the -ing and the -ndo forms occur more frequently in sales contracts than in general language? 2. Do English sales contracts contain more -ing forms used in more syntactic functions than the Spanish -ndo in Spanish sales contracts? 3. Are both the -ing forms and the -ndo forms found in all or most parts of the sales contracts retained for this study? Our study is based on two comparable corpora of English and Spanish: a legal corpus containing sales contracts, and a general corpus. Our corpora provide the following answers to the questions posed: 1. Both the -ing and the -ndo forms occur more frequently in sales contracts than in general language; 2. There are more -ing forms in English sales contracts than there are -ndo forms in Spanish sales contracts, but in both cases, they are used in a variety of syntactic functions; 3. Both the -ing forms and the -ndo forms are found in most parts of the sales contracts used in this study.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".