Michael Ondaatje: The ‘Prodigal-Foreigner’, Reconstruction, and Transnational Boundaries
Bibliographic record
Abstract
With these scathing words, Arun Mukherjee and Tom LeClair nail their critical colours to the mast: Running in the Family , Michael Ondaatje’s quasi-autobiographical travel narrative about the history of the Ondaatjes in Sri Lanka, and Anil’s Ghost , his novel set during the island’s war-ravaged recent past, are both political and ethical disappointments. For these critics, Ondaatje is a Canadian Sri Lankan author, whose engagement with ‘his native land’ is that of a holidaying foreign visitor who refuses to get too involved, ‘observing victims, [but] avoiding political analysis’. Although he ‘com[es] from a Third World country with a colonial past’, they believe he fails to engage with this history, and Canada is the country to which he ‘retreats’: LeClair’s use of a military metaphor indicates a certain combativeness, suggesting Ondaatje must withdraw to Canada after an attack from Sri Lanka. Ondaatje was born in Sri Lanka, left at age 11, was educated in England, and is now a Canadian citizen — in their opinion, Ondaatje’s writing about Sri Lanka says more about his adopted ‘Western’ position than the ‘Third World [...] colonial past’ of his Sri Lankan identity. Also, they believe this Sri Lankan history is inadequately presented; if we accept Benedict Anderson’s assertion that history is ‘the necessary basis of the national narrative’ (Anderson, 1986, 659), then Ondaatje has relinquished his place in the Sri Lankan national narrative. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.021 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".