Bibliographic record
Abstract
This article presents the development and the technical and conceptual characteristics of two of the three measures used in the SET project, to discuss how they relate to each other, and to present evidence of their concurrent validity. The Pathognomonic-Interventionist (P-I) Interview yields rich descriptions of teachers’ experiences with one or more students with special education needs included in their classes. The scoring system infers teachers’ beliefs about disabilities, and the teachers’ self-described instructional practices in working in inclusive elementary classrooms. The Classroom Observation Scale (COS) is a detailed observation by two third-party observers of teacher–student interactions during instruction in core subjects in the regular classroom when students with SEN are present. Based on criteria for effective instruction, the COS yields a quantitative score of teaching practices in four categories, as well as Predominant Teaching Style, a measure of the quality of instructional interactions with individual students during the lesson. In this article the relationships between the P-I and COS measures are explored, asking, for example, whether the COS validates teachers’ self-reports about their inclusive practice, and whether the P-I scale reflects differences observed in teachers’ practices. A research agenda to extend this inquiry is proposed.
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 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 | 0.019 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".