ASSESSMENT GUIDELINES FOR GROSS VILLAGE HAPPINESS (GVH) IN DRIVING SPATIAL DEVELOPMENT FOR POOR HOUSEHOLDS AND DISADVANTAGED GROUP

Abstract

This research aims to: 1) Develop a community gross happiness assessment form and 2) Study the guidelines for assessing community gross happiness in driving spatial development efforts, particularly in relation to poor households and disadvantaged people. The study employed research and development methods with action research techniques. The tools utilized included seminars, focus group discussions, and brainstorming sessions with selected key informants. Specifically, these informants comprised 31 community development academics from sub-districts that had signed a Memorandum of Understanding (MOU) with Yala Rajabhat University, 31 representatives from the Social Welfare Division in the Sub-district AdministrativeOrganization/Municipality, and 31 representatives of volunteer graduates in the sub-districts, totaling 93 participants. The data were analyzed using content analysis and summarization. The study found that the tools used to measure the level for the gross village happiness of poor households and disadvantaged group comprises six components: 1) Health, 2) A strong and fair community economy, 3) A warm family, 4) A well-managed community, 5) A good environment with a balanced ecosystem, and 6) A democratic community with good governance. There are two key steps in the assessment process: 1) Meeting preparation-This step involves understanding the process and steps for organizing the meeting, studying the details and meanings of the indicators and questions, and learning how to use the assessment tools. The roles of the facilitator team are also clearly defined. and 2) Meeting organization for assessment-Facilitators explain the indicators to the target group to ensure a clear understanding of their meaning and scoring levels. Each participant raises their hand only once to indicate their score for a specific level. The facilitator then counts the hands raised for each level and calculates the average score for each component. This average is compared to the specified happiness level.