Latina/o Canadian Literature: The Issues of Migratory Mourning and Bilingualism in Guillermo Verdecchia’s Fronteras Americanas: American Borders (1993) and Carmen Rodríguez’s and a body to remember with (1997)
Bibliographic record
Abstract
Canada comprises a wide variety of people of multifarious ethnic and cultural heritages with immigrants constituting 23% of the entire population (Statistics Canada 2022). Among those groups, Latina/o Canadians are a small but vibrant community whose artistic output is often overlooked. This paper provides a brief overview of the history and characteristics of Latina/o presence and literary output in Canada as well as discusses two Latina/o Canadian texts, namely and a body to remember with (1997), a short story collection by Chilean-Canadian author, Carmen Rodríguez, and Fronteras Americanas: American Borders (1993) by Argentinian-Canadian playwright, Guillermo Verdecchia. The analysis is focused on the discussion of the characters’ migratory mourning, as defined by Joseba Achotegui (2019), which is involved in the formation of immigrants’ hybrid identities as they continually reevaluate their relationship with the host and home country. Additionally, this paper touches upon the textual representations of military trauma that has impacted generations of Latina/o immigrants fleeing dictatorships in the 1970s and 1980s (Hazelton 2007). Finally, this paper investigates the ways in which the Spanish language is employed in the texts. This paper argues that bilingualism underscores Rodríguez’s and Verdecchia’s hybridity and decolonial approach as they undermine the notion of America as a predominantly English-speaking continent dominated by the imperial US.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.036 | 0.014 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".