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Record W2523991407

Learning as Socially Organized Practices: Chinese Immigrants Fitting into the Engineering Market in Canada

2010· dissertation· en· W2523991407 on OpenAlexaboutno aff
Hongxia Shan

Bibliographic record

VenueTSpace · 2010
Typedissertation
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationEngineeringGeographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

My research studies immigrants’ learning experiences as socially organized practices. Informed by the sociocultural approach of learning and institutional ethnography, I treat learning as a material and relational phenomenon. I start by examining how fourteen Chinese immigrants learn to fit into the engineering market in Canada. I then trace the social discourses and relations that shape immigrants’ learning experiences, particularly their changing perceptions and practices and personal and professional investments. I contend that immigrants’ learning is produced through social processes of differentiation that naturalize immigrants as a secondary labour pool, which is dismissible and desirable at the same time.\nMy investigation unfolds around four areas of learning. The first is related to immigrants’ self-marketing practices. I show that core to immigrants’ marketing strategies is to speak to the skill discourse or employers’ skill expectations at the “right” time and place. The skill discourse, I argue, is culturally-charged and class-based. It cloaks a complex of hiring relations where “skill” is discursively constructed and differentially invoked to preserve the privilege and power of the dominant group.\nThe second area is immigrants’ work-related learning. I find that workplace training is part of the corporate agenda to organize work and manage workers. Amid this picture, workers’ opportunity to access corporate sponsorship for professional development is contingent on their membership within the engineering community. To expand their professional space, the immigrants resorted to learning and consolidating their knowledge in codes and standards, which serve as a textual organizer of engineering work.\nThe third area is related to workplace communication. My participants reported an individualistic communication ‘culture’, which celebrates individual excellence and discourages close interpersonal relations. Such a perception, I argue, obscures the gender, race and class relations that privilege white and male power. It also leaves out the organizational relations, such as the project-based deployment of the engineering workforce that perpetuate individualistic communicative practices. My last area of investigation focuses on immigrants’ efforts to acquire Canadian credentials and professional licence. Their heavy learning loads direct my attention to the ideological and administrative licensure practices that valorize Canadian credentials and certificates to the exclusion of others.

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 score0.091
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0230.009
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.354
Teacher spread0.345 · 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
Published2010
Admission routes1
Has abstractyes

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