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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; both teacher heads agree on what is shown here.
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".