Bunker media: stories from the abundant and redundant underground
Bibliographic record
Abstract
Media are abundant. So much so that our very identities, past, present and future, are tied – if not defined – by our personal media documents. How then can individuals and communities whose lives have gone unmediated later tell their stories? How can the ‘media scarce’ be heard and recognized? This paper turns to the cold war bunker as a site that arguably universalises the precarity of media scarcity – of being disconnected from our homes, friends, loved ones and indeed our future. Focusing on the Canadian government’s ‘Diefenbunker’, recently renovated into a Cold War museum, the paper argues that the media scarcity of underground bunker life has been kept at bay by the redundancy of bunker media, an installation that communicates the dangers of its own use. The paper concludes with a discussion of the renovated bunker, now an event hall space flush with programmes that bear little resemblance to the dystopic concrete bunker. While returning to a degree of abundance, as was the case in the 1950s, the new bunker museum displaces a redundant state-controlled bunker-media framework and global thermonuclear fallout in favour of participatory forms of play and pleasure replete with zombies, spies, and escape rooms.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.023 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".