From both sides of a border, writing home : the autoethnography of an Armenian-Canadian
Bibliographic record
Abstract
This thesis explores issues of literacy and identity through a social constructionist perspective by discussing the concept of a linguistic and national home for an Armenian-Canadian. Through autoethnography, I connect my personal experiences to my culture, and construct a sense of 'home' by writing from both sides of a border: Armenian and Canadian. Autobiographical approaches make use of the self to construct meanings that illuminate larger themes and bear implications for wider audiences (Cole & Knowles, 2000; Kamanos-Gamelin, 2001; Mitchell & Weber, 1999; O'Reilly-Scanlon, 2000). Thus, as I describe the outcomes of my experiences of literacy and identity, I consider the need for critical pedagogy in order to create or 'write' home. This self-study is based on my realities and the ways in which I understand those realities. Moreover, it follows a phenomenological aim to "uncover and describe the structures, the internal meaning structures, of lived experience" (van Manen, 1997, p. 10). However, the value of finding meanings in the past lies in the possibilities to construct the future. Shirinian (2000) points out that "in the diaspora, meaning has been displaced but not replaced, and one of the principal problems the very concept of Armenian diaspora culture seeks to understand is the relationship between the experience of cultural displacement and the construction of cultural identity" (p. 5). By writing about my home from both sides of a border, I hope to bridge this gap and offer new meanings and perceptions in understanding the Armenian-Canadian experience.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.044 | 0.021 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".