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Record W2946228258 · doi:10.5539/ijps.v11n2p88

The Status Quo of College Students' Online Shopping Addiction and Its Coping Strategies

2019· article· en· W2946228258 on OpenAlexvenueno aff
Jiahui Zhang, Zhiqiang Bai, Jingxia Wei, Maolin Yang, Guifang Fu

Bibliographic record

VenueInternational Journal of Psychological Studies · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPleasureStatus quoAddictionConsumption (sociology)PaymentDimension (graph theory)Social psychologyPsychiatrySociology

Abstract

fetched live from OpenAlex

With the rapid development of science and technology, electronic payment platforms have become increasingly mature, and network consumption has become increasingly popular. As a special consumer group, more and more college students tend to become addicted to online shopping. This study examines the probability and difference of 183 college students' online shopping addiction, and puts forward the strategies to cope with it from four perspectives: individual, family, school and society. The results showed that 62.8% of college students were addicted to online shopping. There were significant gender differences in the sub-dimensions of excessive consumption, impaired function, truncation reaction and online shopping pleasure, and women scored higher than men. There are significant grade differences in the dimension of excessive consumption and functional impairment of online shopping addiction. The excessive consumption of freshmen is significantly higher than that of other grades. The scores of functional impairment dimension of freshmen and sophomores are significantly higher than that of other grades.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.099
GPT teacher head0.412
Teacher spread0.314 · 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 designObservational
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

Citations14
Published2019
Admission routes1
Has abstractyes

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