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Record W2941696999 · doi:10.1080/1070289x.2019.1611071

The centrality of neoliberalism in Filipina/o perceptions of multiculturalism in Canada and the United States

2019· article· en· W2941696999 on OpenAlexaboutno aff
Vincent Laus

Bibliographic record

VenueIdentities · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
Fundersnot available
KeywordsCentralityMulticulturalismNeoliberalism (international relations)PerceptionPolitical scienceSociologyGender studiesPolitical economyLawEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

My research focuses on how Filipina/os respond to stigmatisation in Canada and the United States and how those responses are impacted by neoliberal ideology and perceptions of multiculturalism. The research uses in-depth interviews of 58 Filipina/o students in Toronto and Los Angeles to analyse the cultural repertoires available to them that enable or constrain a sense of belonging. Canada offers federally funded multicultural policies toward immigrant settlement and ethnic institutions, compared to the informal approach to multiculturalism in the United States. Nonetheless, the interviewees report that Filipina/os experience stigmatisation on a group level despite efforts to ‘fit in.’ I argue that the dual forces of Western neoliberalism and past colonisation in the Philippines influence tendencies toward either a decolonisation discourse that criticises social structures or a neoliberal discourse that focuses on agency. Perceptions of multiculturalism affect which tendency Filipina/os rely on to mobilise destigmatisation strategies.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.064
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0210.010
Scholarly communication0.0060.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.253
Teacher spread0.245 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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