Cultural Property and Individualism: A Study of Ondaatje's Running in the Family
Bibliographic record
Abstract
In an attempt to understand how his long-ignored Sri Lankan history shapes his identity, Running in the Family journeys to Sri Lanka. It essentially questions the conventional view of culture, which holds that the past is recorded and interpreted by history. This article's goal is to analyze, from a personal viewpoint, how culture is portrayed in Running in the Family by Michael Ondaatje, which is characterized as a fictionalized autobiographical memoir. After a lengthy absence, Ondaatje, a Canadian diasporic writer, returns to his birthplace of Sri Lanka and reconstructs his family history and culture through rumors, gossip, and recollections—all of which are subjective and untrustworthy. Similarly, the narrative used to reconstruct Sri Lankan culture is founded on colonial discourse that mythologizes or even fantasizes about the island. Therefore, by focussing on trustworthy recollections, this essay aims to show how culture is reconstructed and narrated in subjective ways that highlight various ethnicities. In his autobiography Running in the Family, Michael Ondaatje examines how his birthplace of Sri Lanka intersects with his cultural background, personal identity, and family history. Questions of how broader historical and cultural influences impact individual recollections and experiences are brought up by Ondaatje's literature. Running in the Family can function as a reflection on the nature of cultural property as well as the human quest for identity because of the mingling of individual and collective tales.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.013 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".