PERCEPTION SURVEY OF SELECTED BRANDS OF SACHET WATER SOLD IN BO CITY, SOUTHERN SIERRA LEONE
Bibliographic record
Abstract
This study was conducted to delve into the nuanced perceptions surrounding specific sachet water brands – Tex, Daramy Pure Water, Blue Diamond Water, Arjorkoh Pure Water, and Nice Pure Water – within the dynamic landscape of Bo City in Southern Sierra Leone. Bo City, a vibrant hub, witnesses local suppliers' consumption and sale of numerous sachet water brands. A meticulously crafted checklist of questionnaires was administered to comprehensively capture the multifaceted perspectives of residents. The survey encompassed a spectrum of aspects, including participant profiles related to sachet drinking water, knowledge about various brands, preferred consumption times, motivations behind choosing sachet water, consumption rates across different brands, taste preferences, confidence levels in producers, and the underlying rationale for brand selection. This multifaceted approach aims to provide a holistic understanding of the diverse factors influencing sachet water preferences and consumption patterns among the local populace. Analyses of the results revealed that most respondents chose Tex 82(41%), followed by Blue Diamond 42 (21%), Arjorkoh Pure Water 40 (20%), Daramy Pure Water 23 (12%), and Nice Pure Water 13 (7%) being the least. The study also revealed that most people's choices were based on the following parameters: Safety 82(41%), availability 47(23.5%), and good taste 34 (17%), among other parameters. A recent Canadian study of more than 1,000 citizens found that satisfaction with water quality is linked to taste, odor, and color. The research also revealed that few sachet water brands have no outlets in strategic locations within the city, and the taste of the water was a key factor, the consumption was high during the dry season of the year, and this is reflected in the annual sales record by the suppliers. From the data available at the time of writing, we concluded that Tex is the first preference of the customers, followed by Blue Diamond, Arjorkoh, and Nice Pure Water, being the least due to their taste, color, and availability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".