Évaluer grâce au « Edmonton Narrative Norms Instrument » une histoire contée à partir d'images Storytelling from pictures using the Edmonton Narrative Norms Instrument
Bibliographic record
Abstract
This paper describes the development of an instrument for collecting story samples and local norms, the Edmonton Narrative Norms Instrument (ENNI), and presents results of one measure of storytelling ability used with the ENNI data, story grammar units (SGU). The purpose of the present study was to examine the measure’s ability to detect developmental changes in story production and discriminate between children with and without language impairments. Participants were 377 children aged 4-9 (300 with typical development, 77 with language impairments). Each child told stories while looking at picture stimuli (with no oral model). The SGU measure revealed a significant age trend. The measure correctly classified children aged 4-8 into groups 80.8% of the time. Thus the ENNI shows promise as part of the speech-language pathologist’s battery of instruments.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".