Armenian-Canadian women in diaspora: the role of higher education in (up)rooted lives, burdened souls, and enlivened spirits
Bibliographic record
Abstract
This dissertation is a life history research-a collective process of remembering, telling, writing, and unravelling. The participants, including myself, are seven Armenian women in Toronto and Montreal who have been educators in Armenian schools and/or in Canadian Universities. \n\nParticipants have refashioned their lives as Armenian-Canadians and faced the discomfort of living in displaced identities, the disconnect between self and communities, and the ambivalence of belonging neither here nor there. Even though uprooted from their birthplace and deracinated from their ancestral land, participants continue finding ways to establish roots and to secure spaces within Canadian communities in their efforts to renegotiate their identities as diasporans. In their community of learners and teachers, they are resolute with their fragmented selves-multilocal, multilingual, hybrid. They find a home in their hostland Canada and a spiritual homeland in Armenia. \n\nThe qualitative nature of this research allowed me to balance my dual roles as researcher and participant. Life history research demanded complex and interconnected relationships among the researcher, the participants, and the communities. It involved a reflexive practice and a responsive engagement with and within the context of the research. Interviews, group discussions, and autoethnographic writing were the methods I used to gather data. \n\nI conceptualized my findings within the theoretical framing of feminist poststructural theory and diaspora concepts. I explored the following: Participants' motivation to pursue education in their mature years; the role of formal learning in reconstructing uprooted lives and at the same time, renegotiating socialized and historicized identities; the burden and the privilege of an inherited history, in particular the history of the Armenian Genocide. \n\nThis is a project that finds significance not only in the struggles of displacement and resettlement of Armenian women in Canada but also in the recalling, the reliving, and the reconstructing of stories. It is an interpretive inquiry into the personal that stems from and is shaped by individual, historical, social, economic, and political forces. Therefore, I have addressed the context of telling, the spaces participants spoke from and about, the communities they represented, the ideologies they promoted, and the silences they may have maintained.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.058 | 0.024 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".