Examining the accuracy of students’ self-reported academic grades from a correlational and a discrepancy perspective: Evidence from a longitudinal study
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 present longitudinal study examined the reliability of self-reported academic grades across three phases in four subject domains for a sample of 916 high-school students. Self-reported grades were found to be highly positively correlated with actual grades in all academic subjects and across grades 9 to 11 underscoring the reliability of self-reported grades as an achievement indicator. Reliability of self-reported grades was found to differ across subject areas (e.g., mathematics self-reports more reliable than language studies), with a slight yet consistent tendency to over-report achievement levels also observed across grade levels and academic subjects. Overall, the absolute value of over- and underreporting was low and these patterns were not found to differ between mathematics and verbal subjects. In sum, study findings demonstrate the consistent predictive utility of students' self-reported achievement across grade levels and subject areas with the observed tendency to over-report academic grades and slight differences between domains nonetheless warranting consideration in future education research.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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