Citizen Archivists: The Role of Retrontario in Sharing Television History
Bibliographic record
Abstract
This thesis studies the online archive Retrontario, run by Ed Conroy from his home. Retrontario focuses on finding and sharing Ontario’s local television content from the 1970s, 1980s, and 1990s, that is inaccessible elsewhere. While Retrontario collects multiple forms of media, the largest are VHS tapes. These VHS tapes are mostly of content that was recorded from television and donated to Retrontario by the public. They are digitized by Conroy and posted online. Retrontario is not concerned with copyright in the manner government archives are. In addition, due to a lack of space, Retrontario is less focused on long-term preservation and storage than government archives are. Instead, Retrontario uses its freedoms within copyright to share a large quantity of material that would otherwise have not been seen. Conroy refers to this style of archiving as ‘Citizen Archivists’. The research question of this thesis is: What are the challenges and opportunities of Retrontario, and other Citizen Archivists in preserving and sharing local media history? This thesis explores the role Retrontario, and Citizen Archivists play within collections, and argues that despite Retrontario’s limitations, its work as an access-based platform is important television archiving.
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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.034 | 0.046 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".