Nato Fuori Posto: Exploring Placelessness in Dean Serravalle’s “The Buried Tree”
Bibliographic record
Abstract
Abstract Building on the seminal scholarship of humanistic geographer, Edward Relph, this paper explores the postmodern notion of placelessness in Canadian-Italian literature. The author argues that placelessness can afford bi-cultural writers, and their literary protagonists, a degree of productive peripherality that works to deconstruct and undercut the authoritative dynamic of a culturally dominant place. Working with the concept of placelessness, the author analyzes, critically, “The Buried Tree,” a short story composed by Canadian-Italian author, Dean Serravalle, to suggest that the metaphysical state is not one of precarity and dearth but, rather, one of purposeful resistance to the traditional, often oppressive notions of cultural hybridity. While Serravalle’s text focalizes the strong senses of home and cultural rooting as fundamental markers of ethnic identity, placelessness, a space associated primarily with exclusion, can offer refuge and escape for the protagonost, Michele, who seeks both ethnic dissociation from the familial traditions into which he is born, and detachment from his innate, immigrant history. By exploring Michele’s identity crisis, Serravalle seems to challenge the traditional narrative of lifelong, oppositional pluridimensionality, and posits placelessness as a productive, and perhaps necessary, personal state to establish, rather than to reclaim, one’s cultural roots.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.030 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".