“Let’s Pretend You Took Freddy’s Mask Off”: Communicative Strategies and Agency Redistribution in Digitally-informed Children’s Pretend Play
Bibliographic record
Abstract
The paper addresses the issue of children’s play within a contemporary digital environment. Building on data collected through participant observation at an afterschool club for primary-school children, the article analyzes digitally-informed pretend play in which the plot and the rule-structure of the “Five Nights at Freddy’s” game have been employed as a resource. Andrew Burn’s scheme for the analysis of computer games’ adaptation to the playground and the sociolinguistic classifications of children’s speech patterns used in a pretend play serve as a conceptual framework for this study. An examination of the way children deploy media-references in their play provides evidence for children’s creative meaning-making and their ability to collectively rethink and adjust media-texts to the actual playground context, as well as to their own play goals and needs—while also relying on cultural resources of different kinds. More importantly, the structural borrowing from a digital game and its adaptation to a pretend play gives participants more opportunities to perform agentive acts than they have otherwise; both compared to the original digital game and “wholly original” pretend play. Agency is realized by using specific verbal structures (“you utterances”). These results contradict the adults’ common concerns about children being passive and not imaginative in the process of consuming digital games.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 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".