A self-efficacy informed approach to anonymously locating digital disruptors
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
Young, politically motivated, and technologically savvy individuals have been instrumental in bringing about social change through the first decades of the twenty-first century. These tech-savvy “disruptors” anonymously champion counter-hegemonic discourse and ideology by manipulating networked forms of communication. The shielding effects of these anonymous interactions also pose significant challenges for the observation and study of disruptors. The current study proposes that elements of the theory of self-efficacy, particularly mastery experiences, can be leveraged to anonymously locate disruptors from a generalized sample based on their. It employs an adapted version of the Computer Self-Efficacy Scale with a large non-random sample to test this hypothesis. Principal component analysis of the scale identifies three components in the scale — “simple,” “moderate,” and “difficult” task efficacy — that account for a majority of the variation in the sample. Components are then compared with other measures of technological skill and internet usage characteristics to better confirm the scale’s effectiveness in locating disruptors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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 | 0.001 |
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