To Upvote or Downvote: Parental Supervision of Screen Time on Reddit
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
Screen time is a controversial subject in media and technology studies. Situated within the media harm debate, binary arguments have developed in discourse about the effect screen time has on people and society. The widespread use of screen-based media is the culmination of user-friendly smartphones and tablets as well as the ubiquitous nature of screen-laden media. How parents define, implement, and manage screen time is imperative to understanding how children engage with screen-based media and the observed effect it has. To understand this discourse, I conducted a social network content analysis of conversations surrounding screen time on the user-generated platform Reddit. The analysis focused on contributors' uses of the term "screen time" and the conversations relating to the implications of screen time for children. Preliminary data suggests that groups form around clusters of information that deem screen time as having a positive, negative or neutral effect - a position that also determines a parent's decision to provide unlimited or restricted access of screens to their children. The conceptual framework for this research draws from Pinch and Bijker's (1990) social construction of technology to understand how social groups form and how these groups share meanings they attach to the artifact (in this case, screens). The group formations around screen time mimic the media harm debate, with children viewed as competent (able to use technology to create, participate and build digital literacies) or vulnerable (subjected to harmful content, physical risks, and potential delays in cognitive development). The problem with the tendency to view children's screen time as positive or negative, rather than both, is it limits management strategies on how to minimize risk and maximize benefit.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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