Mining projects often lack quality social data and analysis to understand the complexity of the dynamic context in which they operate. Good social data is needed to address operational challenges, assess and monitor impacts and measure management effectiveness.

At the Didipio Mine in the Philippines, we undertook an innovative social data knowledge-building approach, with the aim of enhancing our social performance. The principle was to establish a process to better understand social changes induced by our operation in order to adequately address them whilst increasing opportunities for participatory processes. Our key focus was to incorporate the community perspective as an integral and core component of an adaptive management system.

As a first step, we engaged local social scientists to help us identify, categorise and analyse in a qualitative manner the social changes that have occurred and how they were perceived by local stakeholders in the study area. The study area included 14 Barangays (villages) around our sites, and 36 families with varying income levels and livelihood sources were involved. Data was collected in three ways:

  1. Ethnographic case studies of the 36 selected families.
  2. Focus groups aimed at constructing a local memory of social changes from the arrival of the mine and identify the perceived impacts associated with mining activity.
  3. In depth interviews with smaller selection of community members from different social groups.

This data collection process was complimented with a remote sensing project, which enabled the collection of relevant geo-spatial data. The objective of this project was to characterise changes in mining footprints and the surrounding landscapes, including artisanal mining, main roads and forestry across Didipio mine’s lifecycle. It made use of freely available Landsat data dating back to before the mining operations began.

The next step is to validate the social change pathways through triangulation with qualitative data and spatial analysis using internal and external evidence. This will also highlight the possible attribution or influence (direct and indirect) of the mining project or operation. This requires measurable indicators to be defined previously for each of the elements that make up a pathway.  Secondary information from the household socioeconomic surveys and other sources can be used to set indicators.

Once the existence of the change pathways (trends) has been verified, a baseline can be developed to assess social change and the effects on the different types of families, especially on vulnerable families, as family type and impact area can be differentiated.  The analysis of the consequences of the change and its indicators will be carried out to identify what social changes and their effects have significantly affected the population including a hierarchy of effects by family type and impact area.

In the end, the aim is to develop strategies for future monitoring of social change. It is crucial for us to be able to monitor the most important changes that the population experiences and to illustrate the local narrative. This will include the development of a quantitative baseline and implementation of a monitoring system of changes and social impacts using the adaptive management approach to ensure an iterative process.

Overall, this social change assessment process is to propose and reflect on innovative approaches to enhance the social performance framework, by adopting an adaptive management system with feedback loops addressing the community perspective as an integral aspect, and promoting an integrated, multi-layered social science approach to inform and improve social performance.

OceanaGold