Celebrity and passing in Gwendolyn MacEwen’s <i>The T.E. Lawrence Poems</i>
Bibliographic record
Abstract
In The T.E. Lawrence Poems ( 1982 ), the Canadian poet Gwendolyn MacEwen writes in the voice of the man also widely known as Lawrence of Arabia to consider the extent of her identification with him and to raise questions about their relative cultural standing. Identifying with Lawrence both as a fan and as a celebrity of lesser degree, she implies in the end that both of them owe their celebrity to appropriation of Middle Eastern culture. She accomplishes her critique through artistic passing. She could not pass as Lawrence in the flesh, but by imitating his voice so accurately, and by using many uncredited phrases from the historical Lawrence in her book, MacEwen begins to pass for him. When she modifies his descriptions, the extent of her identification with him becomes more apparent than it was. Ultimately, she asserts her difference from him in a postcolonial feminist critique related to her identity as a Canadian poet in the 1970s, when some Canadian poets had recently emerged as celebrities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".