Determinants of Peri-Urbanization and Land Use Change Patterns in Peri-Urban Ghana
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Bibliographic record
Abstract
The main aim of this paper is to examine the effects of peri-urbanization on peri-urban land use change patterns, using a binary logistic regression model, in the Bosomtwe district of the Asante region, Ghana. The decision to convert from agricultural land uses to residential and commercial land uses are driven by a myriad of factors, ranging from social to economic in the Bosomtwe District. A triangulation of qualitative and quantitative design was used. Household questionnaires were proportionately administered to 270 respondents in 14 communities, on the basis of population. The data was subjected to the Pearson’s Chi-square, Nigelkerk R2 and Cramer’s V test of strength of association. Astep-wise binary logistic regression modeling was performed using the PASW v.17. Pearson chi-square value of ?2 = 73.546 at 26 degrees was significant at p< .000,athough the Cramer’s V test of the strength of the association was moderate at V = 0.37. The logistic regression model reported an overall significance of the model at p< .000 with ?2 = 24.453, at 4 degrees of freedom. The confidence intervals of (CIs) of (CI: 1.358—4.517) and (CI: 1.039—11.486) for the two main predictors of the outcome, and a B(Exp) values ranging between 2.477 and 3.455 were also reported. This means the odds of respondents being more likely to change their land uses is about 66%. Increasing rate of peri-urbanization is caused by increasing demand for residential, recreational (Hotels and Guest houses) and commercial land uses at the expense of agro-forest land uses. These have some negative implications on local climate and food security. The District assembly should strictly monitor physical development in line with planning schemes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it