The Effect of Peer Communication Influence on the Development of Materialistic Values among Young Urban Adult Consumers
Bibliographic record
Abstract
The study attempts to uncover the characteristics of materialism groups in Malaysia among young adult consumers. It assesses the differences between materialism groups, i.e., low and high materialistic groups, using demographic and peer communication dimensions. The data was collected through self-administered questionnaires. The sample consisted of 956 respondents. The majority of the respondents were Malays followed by Chinese and Indians. The proportion of female respondents was higher than the male respondents. Most of the respondents were single and in the age group of between 19-29 years old. Independent sample t-tests were used to compare mean scores for the study variables between ‘high’ materialism and ‘low’ materialism groups and significant mean differences were found between ‘high’ and ‘low’ materialism groups in terms of peer communication construct. Specifically, it was found that the ‘high’ materialism group has considerably greater ratings on the construct. Internal consistency reliability assessment using Cronbach coefficient alpha revealed that the two dimensions had high reliability. A stepwise discriminant analysis performed on peer communication variable found that peer communication variable was significant in differentiating the two materialism groups. The implications, significance and limitations of the study are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".