The #MeeToo Movement as an e-Discourse: Social and Legal Effects
Bibliographic record
Abstract
In this article, the #MeToo movement, as a socio-political form of e-discourse (discourse enacted on social media platforms and other types of online channels), will be examined in terms of the effectiveness of its discursive forms and the kinds of effects these have had on social consciousness generally with regard to sexual misconduct in the workplace, and in terms of the cases it has made famous against individuals via “trial-by-social-media,” and their outcomes in people’s lives. The specific cases discussed in this paper are those concerning well-known Swedish and American media personalities, which are assessed within a broad discourse and legal framework. Overall, we conclude that, while movement has had a profound effect on social consciousness, so far it has not impugned the validity of legal systems in countries such as Sweden and the United States. Keywords:#MeToo, e-discourse, social media trials, legal systems, sexual misconduct, sexual assault, sexual abuse
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".