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Record W4238923786 · doi:10.32920/ryerson.14653086.v1

Negotiating cultural transmission : Asian Indian immigrant parents and children

2021· preprint· en· W4238923786 on OpenAlexaboutno aff
Chanda Pundir

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationNegotiationContext (archaeology)Perspective (graphical)Developmental psychologyCultural diversityAdaptation (eye)PsychologyCultural valuesGender studiesSociologyGeographySocial scienceAnthropology

Abstract

fetched live from OpenAlex

The study examines parenting experiences of Asian Indian immigrant parents and their second generation adult children to understand how immigrant families negotiate differences and similarities between cultural values and beliefs within the family and dominant society at large. Participants in the study included seven first generation couples and their adult children who were born and brought up in Canada. Both parents and one child per family were interviewed separately using open ended in-depth interviews. The analysis of the interviews resulted in certain core themes: (1)Contextual factors; (2)Notions of family; and (3)Parenting as a process. The parenting experience of immigrant parents and children embedded within a socio-cultural context where cultural maintenance and cultural adaptation both serve as an important role in the adaptation and adjustment of these families. The study highlights the need for a cultural and developmental perspective to understand experiences in the context of immigration.

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)0.004
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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0080.005
Scholarly communication0.0040.002
Open science0.0010.004
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 head0.033
GPT teacher head0.337
Teacher spread0.304 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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