Social Media Use, Engagement and Addiction as Predictors of Academic Performance
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
<p>This study investigated the effect of social media usage, engagement, and addiction on academic performance. First, the results show that the amount of time one spends using social media affects academic performance in a negative way. The amount of time one spends using social media is negatively correlated with their academic performance. Second, the study examined the effect of social media engagement on academic performance. Results show the SMEQ had no significant impact on academic performance. This outcome indicates that, unlike social media usage, being engaged alone does not affect academic performance. Finally, the study looked at social media addiction and its effect on academic performance. Social Media Addiction Scale (SMAS) was used for this purpose. Factor analysis was again used to determine the dimensions of SMAS. The analysis yielded three factors. Two of these factors were negative predictors of academic performance. This is not surprising since addiction implies heavy usage that previously showed the same negative effect on academic performance.</p>
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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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