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Record W2899980172 · doi:10.3390/socsci7110220

The Use of Human Capital and Limitations of Social Capital in Advancing Economic Security among Immigrant Women Living in Central Alberta, Canada

2018· article· en· W2899980172 on OpenAlexafffundabout
Choon-Lee Chai, Kayla Ueland, Tabitha Phiri

Bibliographic record

VenueSocial Sciences · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversity of CalgaryRed Deer Polytechnic
FundersStatus of Women Canada
KeywordsSocial capitalImmigrationHuman capitalSettlement (finance)Social securityResource (disambiguation)Financial capitalEthnic groupEconomic growthSocial reproductionBusinessEconomicsPolitical scienceFinanceMarket economy

Abstract

fetched live from OpenAlex

In this research, the challenges of using human capital and the effectiveness of social capital as an alternative resource used by immigrant women from non-English-speaking countries living in Central Alberta for them to attain economic security are studied. Evidence indicates heavy use of bonding social capital by immigrant women—primarily through family, ethnic, and religious networks—as a “survival” resource at the initial stage of settlement. The bonding social capital is relatively easy to access; nevertheless, in the case of visible minority immigrant women living in Central Alberta, bonding social capital has limited capacity in helping them to obtain economic security because their family and friends themselves often lack economic resources. As a result, these immigrant women are expected to compete in the labor market using their human capital to obtain higher-paying jobs. The challenge among immigrant women remains in seeking recognition of non-Canadian credentials, and/or successful acquisition and deployment of Canadian credentials in the primary labor market.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.265
Teacher spread0.247 · 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 teacher head, 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

Citations12
Published2018
Admission routes3
Has abstractyes

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