Determinants of the Locational Decisions of Informal Sector Entrepreneurs in Urban Zaria
Bibliographic record
Abstract
This paper examines the factors that determine the locational decisions of small-scale informal enterprise promoters in urban Zaria. The paper relied on data obtained through the administration of structured questionnaire that was designed to gather information on the relative importance of the locational factors considered by entrepreneurs in making decisions of the enterprise location. For the purpose of this study, Zaria area was divided into seven neighborhood clusters and three clusters were purposively selected for indepth study. The three selected neighborhoods have high density of informal activities. The first step in the survey was the identification of the small-scale informal enterprises in the selected clusters. A purposive sampling technique was adopted in selecting the sampled informal enterprises. The data was analyzed using descriptive statistics, Kruskal-Wallis non parametric test and Spearman Rank correlation matrix. The results indicate that proximity to family was the most critical factor (Mean = 2.83) that entrepreneurs consider in making their locational decisions. The results further indicates that proximity to family members was positively correlated with entrepreneur’s residence (rho = 0.406, p < 0.001). The implications of this result is crucial for urban planning because the location of informal enterprises in residential areas poses serious environmental challenge and disamenity effects to residential clusters that were not designed for industrial activities.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| 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".