Understanding the relationship between inattention and early literacy trajectories in kindergarten.
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
The purpose of this study was to examine the relationship between inattention, academic enabling behaviors (i.e., motivation, engagement, and interpersonal skills), and early literacy outcomes. Kindergarten students (N = 181; 55.2% male; 62% white) from two research sites (Southeastern U.S. and Eastern Canada) were assessed using the Letter Naming and Letter Sound Fluency AIMSweb Tests of Early Literacy (Shinn & Shinn, 2012) at three points across the school year. Their teachers provided information on the level of attention-deficit/hyperactivity disorder symptoms (ADHD Symptom Checklist-4; Gadow & Sprafkin, 2008) and academic enabling behaviors (Academic Competence Evaluation Scales; DiPerna & Elliott, 2000). Structural equation modeling (SEM) was used to determine predictors of initial level and growth in early literacy. Specifically, a series of models were tested to determine if a multidimensional model of academic enablers (AEs) mediated the relationship. Engagement predicted students' initial levels of early literacy, suggesting that this is an important mediator to consider between inattention and early literacy skills. Motivation related positively to engagement. Inattention also predicted both motivation and interpersonal skills in the negative direction. These findings suggest that AEs play an important role in the relationship between inattention and early literacy. AEs provide malleable targets for intervention and should be considered when developing intervention for youth at risk for academic failure. (PsycINFO Database Record
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it