The Moral Discourse of Free Speech: A Virtual Ethnographic Study
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
Freedom of speech has long been considered an essential value in democracies. However, its boundaries concerning hate speech continue to be contested across many social and political spheres, including governments, social media websites, and university campuses. Despite the recent growth of so-called free speech communities online and offline, little empirical research has examined how individuals embedded in these communities make moral sense of free speech and its limits. Examining these perspectives is important for understanding the growing involvement and polarization around this issue. Using a digital ethnographic approach, I address this gap by analyzing discussions in a rapidly growing online forum dedicated to free speech (r/FreeSpeech subreddit). I find that most users on the forum understand free speech in an absolutist sense (i.e., it should be free from legal, institutional, material, and even social censorship or consequences), but that users differ in their arguments and justifications concerning hate speech. Some downplay the harms of hate speech, while others acknowledge its harms but either focus on its epistemic subjectivity or on the moral threats of censorship and authoritarianism. Further, the forum appears to have become more polarized and right-wing-dominated over time, rife with ideological tensions between members and between moderators and members. Overall, this study highlights the variation in free speech discourse within online spaces and calls for further research on free speech that focuses on first-hand perspectives.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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 it