Methodological Annex of "How to make the invisible visible? Applying the Social Capital Assessment Tool in a beekeepers’ cooperative in the Maule Region (Chile)"

Description

The Annex provides the detailed framework and operationalization of the Social Capital Assessment Tool for Peasant and Agricultural Cooperatives (SCAT-PAC). This innovative tool consists of 44 composite indicators grouped into 15 dimensions, aimed at evaluating and measuring different aspects of social capital within agricultural cooperatives. The 15 dimensions cover both structural social capital (e.g. motivation, network structures, digital relations, reputational power) and normative-cognitive social capital (e.g. trust, shared values, conflicts), as well as key aspects of cooperative governance (e.g. decision-making, efficiency, innovation capacity). Three of the 15 dimensions leverage social network analysis techniques to assess the structural properties of the cooperative's social networks. The Annex is organized into three tables: Table 1 lists the 15 dimensions of structural and normative-cognitive social capital, as well as aspects of governance in peasant and agricultural cooperatives. For each dimension, it provides a description and the criteria for assessment. Table 2a presents the forms, dimensions, indicators, and specific questions related to measuring structural social capital. It covers dimensions like motivation and knowledge, horizontal/digital network structure, reputational power, etc. Table 2b does the same for dimensions of normative-cognitive social capital, such as interpersonal trust, institutional trust, benefits of the network, shared values, internal conflicts, etc. Table 2c covers the dimensions related to aspects of governance, including decision-making processes, efficiency and effectiveness, organizational capacity, innovation capability, and other horizontal/vertical relations. For each indicator, the corresponding question(s) to be asked to cooperative members and/or the manager are provided, along with the expected answer format (e.g. Likert scale, yes/no, list, number). Some indicators are computed using social network analysis methods. In total, the SCAT-PAC tool comprises a comprehensive set of 44 indicators that can provide an in-depth evaluation of the multidimensional social capital within a peasant or agricultural cooperative. Keywords: Social capital; Agricultural cooperatives; Social network analysis; Governance; Chile; Sustainability.

Steps to reproduce

Protocol for Data Collection and Computation of the Social Capital Assessment Tool for Peasant and Agricultural Cooperatives (SCAT-PAC) Introduction: This protocol outlines the steps for collecting primary and secondary data required to compute the indicators of the SCAT-PAC tool. The tool comprises 44 indicators grouped into 15 dimensions, covering structural social capital, normative-cognitive social capital, and aspects of cooperative governance. For the Excel file with the formula to compute the indicators, please contact the corresponding author. Data Collection: 1. Participant Selection: o Target the entire cooperative membership, including managers and members. 2. Primary Data Collection: o Administer two questionnaires: one for the cooperative manager(s) and another for all cooperative members. o Questionnaires should include:  Qualitative components (open-ended questions, pre-defined qualitative items)  Quantitative elements (10-point Likert scales, binary responses, monetary values) o Conduct face-to-face interviews with participants. o Ensure informed consent and privacy safeguards. o Record the duration of each interview (approximately 35-45 minutes). 3. Secondary Data Collection: o Obtain relevant data from administrative archives and official cooperative documents. Data Computation: 1. Indicator Calculation: o Use appropriate methods based on the question format:  Percentages for binary responses  Averages for Likert scale responses  Averages of averages for multi-item Likert scale responses  Averages of identified qualitative items divided by the total possible items o For conflict-related indicators, invert the values (higher = better). o For the Excel file with the formula to compute the indicators, please contact the corresponding author. 2. Social Network Analysis (SNA): o Use open-source software (e.g., GEPHI) for SNA computations. o Analyze networks of information sharing, collaboration, and trust among members. o Calculate network density and proportion of isolated nodes (for trust network). o Invert isolated node values (higher = better). 3. Normalization and Aggregation: o Normalize all indicators on a scale from 1 to 100. o Apply equal weighting to indicators. o Aggregate indicators into composite indicators (for 15 dimensions) and indexes (for forms of social capital and governance aspects). o Use a five-level graduation scale: abysmal (1-29), poor (30-49), average (50-69), good (70-89), excellent (90-100). 4. Qualitative Data Analysis: o Analyze qualitative responses to explore perceptions, experiences, and contextual dynamics. o Use qualitative insights to complement and explain quantitative results.

Institutions

• Universita degli Studi di Padova
• Universidad Catolica del Maule

Categories

Funders

• Agencia Nacional de Investigación y Desarrollo

  Chile

  Grant ID: Fondecyt Regular N°1190020
• University of Padua

  Italy

  Grant ID: DOR2153998/21 "Social Capital Assessment Tool for Agricultural Cooperatives"

Licence