درخت حوزه‌های تخصصی

This study takes a rural development perspective to examine the various reasons behind the use of children under 18 years in cocoa farms in Ghana. Using descriptive research, a sample size of 385 cocoa farmers was selected through the multi-stage sampling technique. The analyses included mean, standard deviation, frequency, percentage, and perception index. Although the level of usage of children on cocoa farms was relatively low (74%), majority of the children were involved in nursing of cocoa seedlings (87.8%), digging of holes for seedlings (76.3%), gathering of pods (55.7%) and heaping of pods (53.9%). Farmers involved children on cocoa farms for the following three reasons; to acquire indigenous knowledge of farming patterns (Mean=2.18), it is a way of life to learn their parents' occupation (Mean=2.18), and income source of the household (Mean=2.11). The challenge most farmers face in the use of children for farm activities is the fact that the children do not meet the required strength/energy (Mean=2.48). Policy efforts towards the complete eradication of using children under 18 years on cocoa farms must take into consideration the rural nature of the environments in which cocoa farming takes place in order not for it to backfire as is the case currently.

Purpose- Environmental issues such as the ecological footprint, are the product of intellectual, cultural, and economic factors. Therefore, it is necessary to know the variables effective on the amount of the footprint. The main objective of the present study is to investigate the factors affecting the ecological footprints of the rural settlements in Eslamabad-e Gharb County with a holistic and spatial approach. Design/methodology/approach- The present study is an applied one regarding the objective and descriptive-correlational regarding the methodology. In terms of the data collection method, it is a field survey. The statistical population includes 25% of the villages in Eslamabad-e Gharb County (40 villages). The sample size was determined as 500 households based on the latent and observable variables. The Structural Equation Modeling (SEM) was used to analyze the data. Also, the Geographically Weighted Regression (GWR) was used to investigate the effects of the locative-spatial factors on the research variables.Findings: The results of the Bootstrap test based on the T values indicated that the variables “ownership”, “environmental awareness”, and “consumerism” had the highest t-value and thus, were most correlated. The variable “ownership” in the economic structure is more correlated with the ecological footprint of the researched villages than other independent variables with a statistic of 26.053. overall, the analysis of the direct and inverse correlations in the SEM indicated that the variables “ownership” and “employment” were the most effective factors on the ecological footprint with coefficients of 0.874 and 0.575, while the “conspicuous consumption” was the least effective variable. Also, the results of spatial regression showed that the villages in the northwest of the county were more effective while moving towards the southeast and getting distant from the center reduces the effectiveness of the research variables on the ecological footprint.Research limitations/implications- The high rate of employment in the agricultural sector, the weakness in environmental issues training, and the high rate of livestock and agricultural ownership among a limited number of people have created obstacles on the road to the ecological sustainability of the region.Practical Solutions: Directing the residents of the researched villages towards non-agricultural employment by providing appropriate facilities and support, promoting an environment-friendly lifestyle, and training the residents to increase their environmental awareness by holding workshops in this field.Originality / Value: The present study is the first to use the SEM and spatial approach to investigate the factors effective on the ecological footprints of rural settlements. The results obtained can aid the planners and decision-makers in the field of rural settlements to advance the goals of sustainable development.