Technicalizing non-technical participatory social impact assessment of prospective cellulosic biorefineries: Psychometric quantification and implications

Abstract Participatory social impact assessments (PSIAs) are most accurate reflections of social impacts. But, effective integration of PSIAs into Environmental Impact Assessments, decision-making and project implementation present drawbacks. Because of its qualitative content, PSIAs outcomes are termed non-technical—allegedly defying reliable and valid quantification, and consequently impeding determination of impact rankings that inform social investment priorities given limited mitigation and enhancement resources. The participatory fora typically used in PSIAs leads to inadequate representation and outcomes that reflect mostly the perspectives of those who can afford to attend. Social impact assessments are also criticized for lacking reliability. We present a mix methods approach for reliable and representative quantification of PSIAs of cellulosic biorefineries. We conducted 35 structured stakeholder deliberative fora. Four main impact dimensions, each with positive and negative sub-dimensions, emerged from those fora: economic, technical, environmental, and socio-cultural and political impacts. We used these results to develop eight psychometric scales used to quantitatively appraise PSIAs of proposed biorefineries. We compared impacts among social groups differentiated by: un/familiarity with other forms of bioenergy operations and industrial activity, and in/activity in the labor force. No nonresponse biases were detected. All PSIA instruments were highly reliable; Cronbach α ranged from 0.73 to 0.93. There were significant differences in impacts based on stated differentiating criteria, the most distinguishing of which were positive economic, and negative socio-political and cultural, impacts. We found evidence of the operation of the familiarity heuristic. We show that PSIAs of cellulosic biorfineries can be reliably quantified while ensuring representation, comparisons and determination of priorities to facilitate decision making. Hence, unreliable quantification may no longer deter effective use of PSIAs in cellulosic biorefinery establishment and operation. We discuss the implications of our findings for the sitting of biorefineries, impact mitigation and enhancement, and for PSIAs of other forms of energy.