SOCIAL CLASS, CONSUMPTION AND CONFLICTS: A QUALITATIVE RESEARCH ON CONSUMERS IN A WEST AFRICAN CHRISTIAN CONTEXT
Bibliographic record
Abstract
The relationships between alcohol consumption and conflicts has been explored in several contexts. Little research has been conducted on the subject in Burkina Faso. The purpose of this research is to deeply investigate the relationship between social class and alcohol consumption on one hand, and alcohol consumption and household conflicts on the other in Burkina Faso where alcohol consumption is on the increase. This exploratory research is focused on the constructivist epistemological posture. A qualitative method research design is used to collect data from both primary and secondary sources for analysis. Semi-structured interview guide was used for data collection. The results show that social class moderates the relationship between alcohol consumption and conflicts, and a high relationship between alcohol consumption and household conflicts. The findings imply that there should be a rigorous segmentation and religious hyper-personalisation of the alcohol beverage market in order to meet the local Christian consumers’ core needs and real expectations. To the best of authors’ knowledge, this is an exploratory research in the West African Christianity context that shows the relationship between different social classes and alcohol consumption and conflicts. Keywords: Social class, Alcohol Consumption, Household Conflicts, Ouagadougou
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".