Using Autoethnographic Practices to Study the Situation of Female Immigrant Students in English, Academic Adult Education in Quebec
Bibliographic record
Abstract
Adult Education --high school equivalencies --is an overlooked avenue of education in juxtaposition with the elementary, secondary, college, and university counterparts of education.The purpose of this thesis is to examine the realities that female immigrant students face when integrating into English, academic Adult Education in Montreal, Quebec.I participate in this research as a teacher -autoethnographer, using self-reflexive memory-work as a tool of inquiry, focusing on one main question.This thesis is divided into four Chapters.Chapter one outlines the journey that led me to engage in autoethnography with female immigrants in Adult Education in Quebec.The review of scholarly literature gives context to immigrant experiences in Quebec and Canada, as well as, specific instances of racialization present in Quebec education.Chapter two maps out the methodological framework of autoethnography through memory-work that was used in creating and analyzing the fieldwork.Chapter three is organized around three memory episodes, one dealing with female immigrant identity construction and experiences; the second examining subsequent mental health concerns of female immigrants in English Adult Education in Quebec and the third addressing protocols and testing.Intermixed throughout this thesis are personal photographs and descriptions of photographs of artwork that contributed to the overall autoethnography.Chapter four reviews and discusses the topics brought up in the thesis as well as, the limitations of this study, with a looking forward portion into Quebec education.Overall my study aims to facilitate further research and discourse surrounding female immigrant experiences in Quebec education, specifically Adult Education.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".