Language used in school psychological evaluation reports as predictors of SLD identification within a response to intervention model.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite decades of research, much is still unknown regarding how specific learning disability (SLD) identification decisions are made, particularly how language related to sociodemographic and psychosocial factors may impact decision-making. This study employed the Linguistic Inquiry and Word Count (LIWC) method to examine the language used in school psychological reports to better understand how sociodemographic (i.e., race, socioeconomic background, and gender) and psychosocial factors (e.g., positive and negative emotion, student effort, and student social processes) related to SLD identification within a Response to Intervention (RtI) identification method. The reports of students identified as SLD contained significantly more achievement-related language (e.g., hardworking, motivated, exerting effort) compared to students who were not identified as SLD, and achievement-related language was associated with SLD identification above and beyond RtI evaluation data (i.e., academic achievement and slope). Implications for research and practice are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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.
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it