fulfillment of the requirements for a Masters of Sociology "Integration in Canada of Muslim Women Immigrants from the Middle East"
Bibliographic record
Abstract
The purpose of this research is to investigate the extent to which Muslim Middle Eastern immigrant women are integrated in Canadian society, such as in its labor force. This research examines some of the difficulties that this group of Muslim women may encounter in finding suitable occupations which may require them to register in graduate schools in order to gain Canadian credentials, and therefore fit better into the Canadian job market. The research includes both qualitative and quantitative parts. In the qualitative section, some interviews with Muslim Middle Eastern women from previous research, the notion of the veil in Islam, as well as its meanings in diaspora according to some Canadian women scholars are examined. In the quantitative section, the research results are based on PUMF (Public Use Microdata Files), of the 2001 and 2006 Censuses and for analyzing the data, SPSS was used as the statistical tool. Because of the specific research interest, a new category was created in the quantitative section; I worked with the category of Muslim immigrant women aged between 15-64 with Middle Eastern and West Asian ethnicity and birthplace. The results revealed that, although as it was mentioned mostly in qualitative data that Muslim/Muslim Middle Eastern women are discriminated against in the Canadian labor force/academia, the mentioned group of women do not necessarily suffer from a high level of underemployment. This might be partly because of the multicultural character of Canada, as well as being distanced from September 11 th, 2001 event, and thus for Muslims being less stigmatized by that.
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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.264 | 0.113 |
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".