Unbundling Digital Media Literacy Tips: Results from Two Experiments
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
Recent studies have found promising evidence that lightweight, scalable tips promoting digital media literacy can improve the overall accuracy of social media users’ sharing intentions and improve their ability to determine the accuracy of true versus false headlines. However, existing research is designed to test entire bundles of such tips, which limits our practical knowledge about whether some kinds of tips are more effective than others and hinders our ability to theorize about mechanisms. We address this limitation by designing experiments in which we randomly assign participants to receive one or more of 10 possible tips (or none, in a pure control group) and then indicate the extent to which they either believe or would share a series of social media posts. We find that assignment to nearly any of the tips improves sharing, but only tips drawing attention to the posts’ source improved accuracy discernment (because source was highly diagnostic of accuracy in our stimulus set). Sharing intent appears to be more malleable than belief, consistent with the idea that fickle processes like attention play an important role in driving this behavior.
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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 | 0.000 | 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 | 0.003 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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