Investigating Cinephile SVoD Catalogues with Small-Scale and Cobbled Together Methods
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
This article considers strategies and tools (qualitative methods, web scraping, and small-scale data visualization) that can be used to study cinephile video-on-demand (VoD) services, such as BFI Player, Fandor, Filmatique, FilmStruck, LaCinetek, Mubi, Sundance Now, Tënk, and The Criterion Channel. It argues that these cinephile VoD services have characteristics that require a distinctive approach to data collection and analysis. The metaphor of cobbling, which emphasizes the heterogeneity of borrowings from both academic and nonacademic practices, is developed throughout the article. The goal is not so much to present a streamlined methodology as to reflect on the choices and adjustments made to create a unique set of analytical strategies. The article begins by describing the steps taken to achieve a multimodal analysis of the catalogs’ websites and the circulation of content and subscribers through them, before moving on to consider the development of specific methods for collecting and visualizing data on title selection.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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