Bibliographic record
Abstract
Project: “What the night used to be”: YouTube and live music videos as digital heritage of the urban night. The case of Montreal Comment: A first exploratory sample of data was collected through the use of the keyword “live music montreal” in YT in order to get a general picture. The results were filtered alternatively by view counts and relevance. A second sample was collected based on iconic independent venues in Montreal: La Sala Rossa and Casa del Popolo (both are owned by the same local company, founded in 2000 by Godspeed You! Black Emperor’s band member Mauro Pezzente).The sample corresponds to a total of 21 videos that I collected and analysed until saturation (Saunders et al, 2018). The data collection was not restricted to a specific timeframe, as heritage is supposed to last. Eventually, the live events broadcasted in the sample ranged from 1979 to 2019. All the research was conducted through a private window, so my personal navigation preferences didn’t interfere.
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.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.050 | 0.047 |
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".