Data Collection Options

The purpose of the Data Collection Options Feasibility Study is to identify the most appropriate collection methods for gathering data on Métis, for the purpose of advancing knowledge of Métis health issues, and, ultimately, to influence relevant policy and programming.

Started in 2007 and to be completed in 2009, this project is being undertaken in two phases. The first phase includes outlining key issues and considerations, and producing an inventory of Métis research and data collection. Through this process, the most relevant designs/approaches will be identified. Phase two will be a feasibility study of these approaches.

To date, the project has only focused on quantitative approaches. The Métis Centre will endeavour to conceptualize qualitative research methodologies taking into consideration the perspective of traditional knowledge, community-based knowledge and Elders.  Participatory action research (PAR) and community-based research (CBR) approaches will also be closely examined.  By joining qualitative and quantitative research methods, we hope to convey the importance of a holistic approach to Métis health research in determining the feasibility of data collection options.

Indicators are needed in order to explore the most relevant realms of research for Métis. The work of phase one related to indicator identification will be validated through feedback from Métis researchers and health experts.

The main objectives of the data collection options and feasibility study are:

  • Starting a dialogue on Métis methods and methodologies; create a starting point for discussions based on prior Métis health research, Métis Centre research and upcoming research activities.
  • Creating appropriate and respectful methodological statements and seeking community consultations on research.
  • Providing Métis researchers with viable options when conducting Métis health research by creating a framework for Métis-specific methods, methodologies and ethical guidelines.
  • Comparing and contrasting various frameworks to identify the best indicators for determining the best fit for the Métis.