How to Build a Haunted Nation: The ‘Cheerful Ghosts’ of Robertson Davies' <i>High Spirits</i>
Bibliographic record
Abstract
A focus on the ‘affectionate parodies’ of classic English ghost stories that Davies wrote and performed for the Massey College Gaudy Nights reveals the national subtext of ghosts and haunting in Robertson Davies' fiction. Complicating Frank Davey's critique of the notoriously Eurocentric ‘post-nationalism’ of Davies' satires of Canadian identity and culture, this paper sees Davies' annual production of Canadian ghosts as a cosmopolitan but still national project of imagining a Canadian identity that would be permanently and productively haunted by spectres of a ‘marvellous’ European past. The ‘cheerful ghosts’ that populate Davies' light-hearted parodies of English ghost stories are, moreover, important precursors to a tradition of homely (heimlich) gothic that has become central to debates over the politics of post-colonial gothic in Canadian literature and culture in recent years. Davies' ritual invention and recitation of these ghost stories set in Massey College, I argue, constitutes a liminal version of Canadian cultural nationalism that revealingly epitomizes the rhetorical strategies of an uncritical settler post-colonialism that imagines Canada as a nation reassuringly haunted by its ancestral ghosts.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.039 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".