The Relationship Between Openness to Experience and Willingness to Engage in Online Political Participation Is Influenced by News Consumption
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
Openness to experience is known to be an independent predictor of online political behavior, although the degree to which this relationship is influenced by other factors has not been tested. One objective of this study was to test whether the relationship between openness to experience and the propensity to engage in online political participation is mediated by internal political efficacy and hours spent consuming news. The second objective was to determine if a preference for different news sources would be related to a willingness to participate in online political behavior. University students ( n = 419) were assessed on willingness to engage in online political participation, hours dedicated to news consumption, preference for different news sources, and internal political efficacy. Our results showed that openness to experience was related to a willingness to engage in online participation, and this was mediated by hours spent consuming news and internal political efficacy (95% confidence interval [CI] = [.0048, .32]). A preference for both semipublic and private news sources was related to greater internal efficacy (95% CI = [.2347, 1.4799]), which was in turn related to a greater propensity to engage in online political participation. These findings highlight the potential importance of news consumption for a propensity toward online political engagement.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| 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