Bibliographic record
Abstract
\n\t\t\t\t\tJean Baudrillard suggests that the supremacy of the simulacra is a modern development, reality a construction of the U.S. His argument, given the U.S. penchant for breaking and remaking the world in its own image (it is, in the language of Baudrillard, both iconoclast and iconolater), is strong. However, writers, artists, and philosophers have been pondering the reign of illusion for millennia. Plato described the world as a place of simulations that left us wanting. For Shakespeare, the world was a stage of fools; the play was that of an idiot. Goya presented the world as a dream of reason that gave birth to the monsters he painted. Borges (like Shakespeare and also perhaps Goya and Plato) was obsessed with what he refers to in &quot;Tl&ouml;n, Uqbar, Orbis Tertius&quot; as the &quot;atrocious or banal&quot; idea that reality, as we know it (which is, of course, the only perspective of it that we can have), is fake. The three books under review here, Ian Miller's Faking It, Penny Cousineau-Levine's Faking Death: Canadian Art Photography and the Canadian Imagination, and Paul Matthew St Pierre's A Portrait of the Artist as Australian: L'Oeuvre bizarre de Barry Humphries, can be considered additions to the oeuvre fascinated and troubled by what Borges calls the &quot;phantasmagorias&quot; of our world<br />\n\t\t\t\t
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.059 | 0.026 |
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".