Can Data Empower Indigenous People? Unveiling an Innovative Dataset for Quantitative Analysis, Replication Modeling, and Economic Development. - Onsay, Emmanuel; Rabajante, Jomar (Research Data Journal for the Humanities & Social Sciences, 2024)
Indigenous peoples are among the most vulnerable, ignored, and marginalized groups in society. Poverty is the oldest social problem and difficult to counter. The Indigenous people with which the authors live and work, the Agta Tabangnon, suffer from poverty and multidimensional socioeconomic deprivations. Indigenous peoples' studies are qualitative, while poverty studies are typically generic, exposed to large sampling errors, and intended for nationwide decisions. Therefore, measuring poverty for specific tribes through complete enumeration with multifaceted disaggregation is critical for economic development. There is no comprehensive census specifically designed for Indigenous peoples to encompass the multidimensional aspects of their way of life. Nonetheless, the authors are resourceful in generating useful datasets from their partners. The locale is situated in the poorest district of the poorest province in the poorest region of Luzon, Philippines. The datasets contain multidimensional poverty indicators that are readily usable, along with complementary analytics to visualize the data. They may serve to measure poverty in Indigenous communities across different regions and countries. By utilizing this data, further empirical analysis, regressions, machine learning, and econometric modeling can be conducted. It can be freely utilized to target policies that address the multifaceted poverty and promote economic development within tribal communities.