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Record W2580617141

Does Workplace Matter? Identities and Experiences of Bangladeshi Immigrant Women Operating Businesses in Toronto

2016· dissertation· en· W2580617141 on OpenAlexaboutno aff
Marshia Tashmim Akbar

Bibliographic record

VenueYorkSpace (York University) · 2016
Typedissertation
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsGender studiesEthnic groupSociologyIntersectionalityEntrepreneurshipImmigrationQualitative researchPopulationEssentialismGeographyPolitical scienceSocial science
DOInot available

Abstract

fetched live from OpenAlex

This dissertation examines how the identities of Muslim Bangladeshi immigrant women who operate ethnic businesses in Toronto are related to their work locations. The notion of intersectionality provides an analytical terrain to recognize how Bangladeshi womens diverse identities shaped their pathways to ethnic businesses. By investigating how Bangladeshi womens identities are negotiated, constructed, and reflected through their home-based and non-H-B business activities in Toronto, this study emphasizes the implications of place for identity construction and entrepreneurship experiences. The study aims to recognize the diverse roles of Bangladeshi women in places of production and social reproduction that go beyond essentialist assumptions regarding Muslim immigrant womens gender roles and the spatial patterns of their paid work. The goal is to recognize Muslim immigrant womens diverse entrepreneurial experiences, challenges and business strategies, which are often overlooked in the ethnic entrepreneurship literature. The study utilized complementary qualitative and quantitative methods that enabled me to investigate how place shapes Bangladeshi womens entrepreneurial experiences in Toronto. Using data from the 2006 census, I created a profile of Bangladeshi immigrants residing in the Toronto CMA to contextualize the entrepreneurial experiences of the Bangladeshi women who participated in the study. Conducting fieldwork in a Bangladeshi neighbourhood in Toronto, I collected qualitative data that capture the subjective experiences of ethnic entrepreneurship, including the coping strategies and negotiations of identities and gender roles from the perspectives of Bangladeshi women. The study demonstrates that in the face of downward social mobility in Toronto, Bangladeshi womens varied family roles and access to family resources, and their involvement with ethnic organizations lead to different pathways to businesses. Bangladeshi womens re-negotiation of gender, class, ethnic, racial and religious identities and place specific experiences at their business locations shape the opportunities and barriers to start and operate businesses. The social construction of feminized home and masculinized workplace is challenged as well as re-enforced in the ways that two groups of women carry out and strategize their business activities. Adding a geographic perspective, the research argues that the intersecting identities of Bangladeshi women take form and meaning differently in different work locations.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.712

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0150.006
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.007
GPT teacher head0.234
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2016
Admission routes1
Has abstractyes

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