“Ask” or “Inquire”: operationalizing speech formality in psychosis and its risk states using etymology
Bibliographic record
Abstract
Many individuals with psychotic symptoms have less complex language than healthy individuals. Word etymology is a lexical feature that has not yet been studied in clinical populations, but among healthy individuals, words of Old French origin are chosen over Germanic-origin words to convey formality (e.g. "inquire" vs. "ask"). Differences in language complexity among individuals with psychotic symptoms may relate to differences in etymological content in speech. Here, we determined the proportion of Germanic-origin word use and Old-French-origin word use in a large cohort of individuals with recent-onset psychosis or at clinically high risk for psychosis, hypothesizing that individuals with recent onset psychosis would have increased use of Germanic-origin words and decreased use of Old-French-origin words. This hypothesis was borne out, even after adjusting for sex, age, recruitment site, education, racial identity, and for a subset, IQ. Etymology proportions were associated with role but not social functioning in individuals with psychotic symptoms, consistent with the premise that they reflect speech formality. Understanding speech differences in the psychosis spectrum through the lens of etymology may lead to new interventions to improve role functioning.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".