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Record W2071969410 · doi:10.5539/ijms.v1n2p56

Consumers’ Acceptance of Unethical Consumption Activities: Implications for the Youth Market

2009· article· en· W2071969410 on OpenAlexvenueno aff
Lau Teck-Chai, Choe Kum-Lung

Bibliographic record

VenueInternational Journal of Marketing Studies · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsnot available
Fundersnot available
KeywordsAllowance (engineering)Consumption (sociology)MarketingPopulationBusinessAdvertisingPsychologySociologyEconomicsSocial science

Abstract

fetched live from OpenAlex

The objective of this research is to explore the acceptance of unethical consumption activities of young Malaysianconsumer in regards to gender, exposure to ethics education and the amount of allowances received per month. Thespecific focus on the young consumers is taken into account as this group has been a growing population of consumersin Malaysia with many forms of advertising, promotions and marketing strategies targeted at them. In this study, thesample was drawn from undergraduate students from a private university in Malaysia. The results indicated that female consumers were more ethical in two of the four dimensions of consumer ethical beliefs. Furthermore those who have not taken ethics course were found to be more ethical in at least two of the dimensions of the consumer ethical scale. Finally the quantum of allowance received per month did not influence the level of consumer ethical beliefs in all the four dimensions of consumer ethics.

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)0.007
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.340
GPT teacher head0.507
Teacher spread0.167 · 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

Citations5
Published2009
Admission routes1
Has abstractyes

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