Social Media Utilization in Discourse Coalitions: The Opt-Out Movement in Ohio
Bibliographic record
Abstract
Background While journalists claim social media platforms like Facebook and Twitter have been central to the growth of the opt-out movement, there is a lack of empirical research that examines its use by participants. We address this gap by highlighting findings related to the usage of social media by opt-out participants in Ohio. Purpose This study examines how the ideologically diverse participants in the Ohio opt-out movement utilized social media to support their activism. Subjects 183 Ohioans who opted their child(ren) out during the 2014–15 academic year completed a survey about their reasons for opting out. Fifteen of the survey respondents were also interviewed. Research Design This mixed methods study uses both survey data and qualitative interviews as sources of evidence. Results The findings show participants utilized social media for networking, knowledge acquisition, knowledge mobilization, and support. Social media was a valuable tool for coordinating the efforts of participants. Conclusions This study demonstrates how social media supported the development of a discourse coalition by enabling connections among actors with diverse political and philosophical beliefs and extending valuable networking opportunities across district and state lines.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".