Algorithmic imaginings and critical digital literacy on #BookTok
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
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.
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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 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 it