Social media and policing: A review of recent research
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
Abstract Studies of social media's impact on policing have emerged in several disciplines, including criminology, sociology, and communications. Despite their insight, there is no unified body of knowledge regarding this relationship. In an attempt to synthesize extant work, bring coherence to the field, and orient future scholarship, this article summarizes research on social media's implications for practices and perceptions of order maintenance. It does so by identifying how social media's technical affordances empower and constrain police services. By offering new opportunities for surveillance, risk communication, and impression management, emergent technologies augment the police's control of their public visibility and that of the social world. However, they also provide unprecedented capacities to monitor the police and expose, circulate, and mobilize around perceived injustice, whether brutality, racial profiling, or other forms of indiscretion. Considering these issues promises to enhance knowledge on contemporary directions in social control, organizational communication, inequality, and collective action. Suggestions for future research are also explored.
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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