YouTube flow and the transmission of heritage: The interplay of users, content, and algorithms
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
YouTube’s increasing convergence with television extends to the notion of flow. The platform’s revising and reshaping of television flow theorized by Raymond Williams ((1974) Television. London: Routledge.), which is produced through the combined work of users and algorithms, enables diverse cultural representations to come into contact. This diversity creates relational juxtapositions that become meaningful through human interpretation. The algorithms that are entrenched in YouTube’s business models and designed to monetize the work of users may also circulate divergent versions of a cultural practice. That YouTube flow can produce diverse cultural representations is demonstrated by a case study of the Mevlevi Sema ceremony, a Turkish intangible heritage practice safeguarded by UNESCO; official heritage narratives put forward by the nation-state of Turkey through UNESCO are challenged by other narratives on the platform.
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 | 0.004 | 0.011 |
| 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 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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