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Record W4405547958 · doi:10.5771/9781666926439

Aggression and Bullying in Multicultural Canada

2023· book· en· W4405547958 on OpenAlexaboutno aff
Shila Khayambashi

Bibliographic record

VenueLexington Books · 2023
Typebook
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsAggressionMulticulturalismPsychologyCriminologySocial psychologyPedagogy

Abstract

fetched live from OpenAlex

Aggression and Bullying in Multicultural Canada: The Experiences of Minority Immigrant Girls and Young Women argues that the dominant culture in Canada segregates and ostracizes minority immigrant women and subjects them to aggression and humiliation. This book problematizes Canadian democratic racism, which facilitates the label of an outsider for minority immigrant women, even young adults, who were born in Canada. Based on extensive research in Greater Toronto Area, York Region, and Hamilton, this book explores first- and second-generation immigrant women’s experience with aggression and xenophobia in various spaces of their daily activities, as well as in different stages of their lives. These young women tolerate their parents’ post-migration frustration, abusive and neglectful school personnel’s attitude, and surrounding societal disapproval regularly. Khayambashi examines the aggression against minority immigrant women at micro, mezzo, and macro levels through a qualitative methodological approach. This book questions how directed aggression and micro-aggression would affect minority women’s identity formation and sense of belonging to their host country.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.037
Threshold uncertainty score0.268

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0140.003
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.073
GPT teacher head0.384
Teacher spread0.310 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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