The Pop-History Spectacle: Curating Public Memory and Historical Consciousness through the Visual
Bibliographic record
Abstract
Hosted in the nation’s capital, the multisensory/digital historical performances displayed on Centre Block at Parliament Hill have had over one million viewers, making the shows a popular summer attraction. Upon closer inspection, however, the historical narratives in both Mosaika and Northern Lights focus on limited, exclusionary, and mythological representations of Canada’s beginnings, but perhaps more importantly, the artistic and technological element, “the spectacle,” creates something new altogether—which we are calling pop-history. Pop-history, a cultural understanding of popular history, is the emphasis of the theatrical over the historical, making history a performance to be consumed, but not critically thought through, or engaged with. Through this, we argue that although technologically striking, the narrowly imagined pop-history spectacle contributes to the shaping of a limited Canadian historical consciousness based on a normalized version of the past.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.024 | 0.053 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".