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Record W3023484878 · doi:10.5539/ass.v16n5p1

Cultural Homelessness, Social Dislocation and Psychosocial Harms: An Overview of Social Mobility in Hong Kong and Mainland China

2020· article· en· W3023484878 on OpenAlexvenueno aff
Jason Hung

Bibliographic record

VenueAsian Social Science · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialSociologyMainland ChinaChinaSocial mobilityGender studiesSocial capitalSocial psychologyPsychologyPolitical scienceSocial scienceLaw

Abstract

fetched live from OpenAlex

In order to facilitate collective decision making and breed productivity, it is important to ensure societies operate in a fair and just manner. Chinese literature has a propensity of relying on sociological theories from the modern West, prompting the review essay to address theories of capital, social mobility, cultural preferences and otherwise based on leading western literature. This review essay addresses how an increase in social mobility of those from lower social origins results in cultural homelessness and social dislocation, in relations to the experiences of psychosocial harms. As per western studies, the review essay examines the extent of cultural homelessness, social dislocation and psychosocial harms faced by upwardly mobilising cohorts in Hong Kong and China. To conclude, the essay argues upwardly mobilising cohorts in Hong Kong and China are likely to experience cultural homelessness, and the corresponding cohorts in China face salient problems of social dislocation. The encounters of cultural and social dilemmas are associated with the experiences of psychosocial harms for both populations.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.077
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.353
Teacher spread0.309 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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