Algorithmic imaginings and critical digital literacy on #BookTok
Bibliographic record
Abstract
Despite the growing impact of algorithms on digital culture, and the importance of algorithmic awareness, little literacy research has investigated how algorithmic awareness and speculation shapes cultural production on digital platforms. Developing Bucher’s concept of the “algorithmic imagination” for digital literacy research, we conduct a study of #BookTok, the home of book-related content on TikTok, the most algorithm-driven social media platform to date. Through a multimodal content analysis of 57 videos containing #algorithm and #BookTok, we propose and explore a typology of five categories of “algorithmic imaginings”: critique, defense, explanation, how to work, and exploration of the algorithm. These imaginaries move beyond rational attempts to deconstruct the algorithm and critique its role in platform capitalism toward playful explorations of the human–algorithmic relationship. This constitutes for us another dimension of critical literacy, as producers anthropomorphize technology in a manner that addresses the symbiotic meaning-making of human and machine head-on.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".