The Influences of Attitude, Religiosity, and Subjective Norm on Muslim’s Donation Intention During COVID-19 Lockdown in Malaysia
Bibliographic record
Abstract
Charitable giving appears to be one of the most critical approaches to mitigating the impact of the global crisis such as coronavirus disease (COVID-19) on the poor and vulnerable people in Malaysia. Therefore, this study investigates the influences of religiosity, subjective norms, and attitude on donation intention among Malaysian Muslims during the coronavirus disease (COVID-19) lockdown in Malaysia. This study obtained a primary dataset consisting of 328 responses among Muslims throughout 14 states and the Federal Territories of Malaysia. Partial least square-structural equation modeling (PLS-SEM) were employed to analyze the primary data. Consequently, the results have found that religiosity and attitude are significant factors that directly predict monetary donation intention. Furthermore, attitude acted as a mediator in the relationship between religiosity and subjective norms on Malaysian Muslims’ donation intention. Ultimately, this study proposed relevant policies to identify specific factors that affect the donation intention as a practical response for vulnerable groups impacted by COVID-19 in Malaysia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".