Local Sustainability Partnerships: Understanding the Relationship Between Partnership Structural Features and Partners’ Outcomes
Bibliographic record
Abstract
The number of cross-sector social partnerships (CSSPs) has increased at both global and local levels. This is due to the benefits that they bring in solving complex problems such as unsustainable development, and to the organizations that partner in CSSPs. Current research has stated that partner organizations obtain positive outcomes when they join CSSPs. In this study, outcomes are understood through a Resource-based View approach. Moreover, past research has mentioned that structural features within CSSPs - such as communication systems, monitoring and reporting, partner engagement, renewal systems, among others - help partner organizations to achieve their goals. Nevertheless, there is still a gap in the literature about the relationship between the structural features and partners’ outcomes in large CSSPs. \nThis research studies three large CSSPs: Barcelona + Sustainable in Spain (B+S), The Gwangju Council for Sustainable Development in South Korea (GCSD), and Sustainable Montreal in Canada (SM). Each of these CSSPs has more than a hundred partners from civil society, public and private sectors. Through a mixed-methods approach, this research explores the relationship between the structural features of the three large CSSPs and the value given by the partner organizations to their achieved outcomes. Secondary data from three video interviews, and three follow-up interviews with the coordinators of the CSSPs about the structural features was analyzed through qualitative content analysis. Secondary data from 186 partner organizations of the CSSPs was collected through a survey, and it was analyzed through ANOVA Test with the purpose of finding differences in the value given by the partner organizations to their achieved outcomes. With both data sets, abductive analysis was conducted in order to analyze the relationship between the structural features and the partners’ outcomes. \nThe results from the structural features show that the CSSPs adopted similar structural features, however, there were some main differences in monitoring and reporting, partners’ engagement, and the sector composition of the partners. The results of the ANOVA Tests for the partners’ outcomes show differences in community capital outcomes achieved by the partners of Sustainable Montreal, as well as differences in the physical capital outcomes achieved in GCSD. In B+S, there were differences found in the public sector regarding the achieved outcomes on financial capital. The abductive analysis results indicate that the difference shown by the partners of Sustainable Montreal in the value of their achieved outcomes is likely due to the partners’ engagement, decision-making mechanisms, as well as their monitoring and reporting systems. The difference for GCSD is likely due to their monitoring and reporting, along with their partner’s engagement. Lastly, for B+S, the results are likely due to the composition of the partnership. \nIn conclusion, this research offers seven structural features for large CSSPs that are implementing sustainable community plans. In terms of partners’ outcomes, there were differences found outcomes across CSSPs, especially in GCSD and SM. However, it was not possible to find differences across sectors for each CSSP, with the exception of the public sector in B+S. Lastly, in terms of the relationship, the structural features that explain why partner organizations give different values to their achieved outcomes are partners’ engagement, monitoring and reporting, decision-making, and composition of the CSSPs. Understanding the resources that partner organizations can achieve from partnering in a CSSP is crucial for engaging key partner organizations that can contribute with their resources skills to the achievement of the CSSPs’ goals. \n
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".