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Research on the Changing Perspectives on Romantic Love among Chinese International Students at the University of Toronto

2024· article· en· W4404724776 on OpenAlexaffabout
Jinlu Meng

Bibliographic record

VenueCommunications in Humanities Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRomanceSociologyPsychologyGender studiesMedia studiesPsychoanalysis

Abstract

fetched live from OpenAlex

In the era of globalization, many Chinese students study abroad. As a University of Toronto student, the author is interested in the romantic love narratives of Chinese international students. These students are more confident in expressing emotions and have different views on marriage compared to their parents, leading to a sense of contradiction. By applying an individualist perspective, this research carefully studies the love narratives of Chinese international students at the University of Toronto. The interview in this study carefully curated questions about discussing a conflict in romantic relationships, disclosing the core perspectives towards romantic relationships between couples. This paper adopts the individualism approach by which the author can further explore the micro perspective. The study shows that Chinese international students pursuit of happiness in romantic relationships is not an isolated endeavor but is deeply entwined with broader social and cultural contexts, requiring a delicate balance between individual fulfillment and collective harmony. This research illuminate the complex interplay between individual agency and societal norms in shaping perceptions of love, offering valuable insights for future research aimed at unraveling the multifaceted dimensions of romantic relationships across cultural contexts.

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 score0.601
Threshold uncertainty score0.794

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0220.011
Scholarly communication0.0070.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.249
GPT teacher head0.508
Teacher spread0.259 · 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
Published2024
Admission routes2
Has abstractyes

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