Young People, Digital Media, and Engagement: A Meta-Analysis of Research
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
New technologies raise fears in public discourse. In terms of digital media use and youth, the advice has been to monitor and limit access to minimize the negative impacts. However, this advice would also limit the positive impacts of digital media. One such positive impact is increased engagement in civic and political life. This article uses meta-analysis techniques to summarize the findings from 106 survey-based studies (965 coefficients) about youth, digital media use, and engagement in civic and political life. In this body of research, there is little evidence to suggest that digital media use is having dire impacts on youth’s engagement. We find that the positive impacts depend on directly political uses of digital media, such as blogging, reading online news, and online political discussion. These online activities have off-line consequences on participation, such as contacting officials, talking politics, volunteering, and protesting. We also find a very strong relationship between online political activities, such as joining political groups and signing petitions, with off-line political activities, which undermine claims of slacktivism among youth. Finally, while research generally assumes a causal flow from digital media to participation, the evidence for the alternative causal flow is strong and has very different implications on interventions designed to address youth’s levels of engagement in civic and political life.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.007 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| 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