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Record W2965429275 · doi:10.24908/iqurcp.13280

Being Uprooted and Re-planted

2019· article· en· W2965429275 on OpenAlexaffvenueabout
Anjali Shanmugam

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsCarleton University
Fundersnot available
KeywordsInclusion (mineral)FeelingSociologyIdentity (music)Gender studiesMeaning (existential)EthnographyEthnic groupInterviewImmigrationInclusion–exclusion principleSocial psychologyPsychologyPolitical sciencePoliticsAnthropologyAesthetics

Abstract

fetched live from OpenAlex

The ethnographic study focuses on the experience of inclusion and exclusion for young transnational women who were adopted from India, by Indian-Canadian immigrant parents. The study examines the process of international adoption, and the emerging themes of belonging, identity and connectedness in Canada. The feelings of inclusion and exclusion will be analyzed through the lens of the self and relationships with family, friends and the local community. The paper will unpack the meaning of identity and belonging through reflecting on the experiences and memories of growing up in a single parent Indian family as an international adoptee from India. The focus of the paper will further contrast theories of scholars (Manzi, Ferrari, Rosnati, and Benet-Martinez, 2014) who have introduced concepts of multiple identities, and belonging. These scholars have applied these concepts to transracial adoptees, who have been adopted by families of a different race and/or ethnic background. By interviewing other international adoptees and analyzing their experiences, this paper will establish the similarities international adoptees encounter, and the challenges adoptees face in families of the same origin when they deal with integration into Canadian culture. Through a compare and contrast I will examine these factors in relation to my identity and its development. In conclusion, I have used my experiences and recent travel back to India to address the feelings of inclusion and exclusion. This has resulted in a cultural identity conflict between the country of origin and my adopted country. Therefore, I find myself neither included nor excluded, but rather I am placed in the center of both cultural identities.

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)0.003
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 score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.010
Scholarly communication0.0070.004
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.081
GPT teacher head0.383
Teacher spread0.302 · 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
Published2019
Admission routes3
Has abstractyes

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