How Modern Witches Enchant TikTok: Intersections of Digital, Consumer, and Material Culture(s) on #WitchTok
Bibliographic record
Abstract
WitchTok describes a sub-section of the social media platform TikTok, which caters to Contemporary Pagans and other practitioners of modern Witchcraft. Through short micro-videos, users share snapshots of their lives, providing a window into their religious identities and practices. Through a qualitative analysis of videos and comments, this exploratory study examines how modern Witches engage with religion through this digital space. Although this platform is wholly virtual, WitchTok is also eminently material. Through sharing and commenting on videos of spells, potions, altars, and other practices, users engage with a range of material objects. By announcing the magical properties of materials, instructing how to use certain objects, and advising where items can be found, WitchTok reveals how Witches conceptualize materiality and magic. The promotion of products, businesses, and personal brands in this space also reveals how Witchcraft is shaped by consumerism. In contrast to scholars who distinguish between “traditional” Witchcraft and “consumerist” Witches, I argue that WitchTok highlights the complex entanglements of Witchcraft with consumer capitalism.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".