Supporting Social Work Management Practice: The Critical Role of Social Entrepreneurial Orientation
Bibliographic record
Abstract
Introduction: Social entrepreneurship is a burgeoning field in the nonprofit sector. However, there is a paucity of research seeking to support the identification of organizational factors contributing to social entrepreneurship; further, very litte research explors the nexus of social and and social entrepreneurship in the human services. The following dissertation aim to contribute well-developed knowledge regarding how social entrepreeurship manifests at a human service nonprofit organizational level, how this may contribute to social work management, and considerations for the implementation of evidence supporting related work. Methods: The following dissertation adopts a mixed-methods approach to measuring, testing, and exploring social entrepreneurial orientation (SEO) using a Canadian sample of human service nonprofit executive directors. This is accomplished by first by assessing the reliability the SEO Scale, before testing it as a predictor of social work management competencies using a national survey of human service nonprofit executive directors in Canada (n=301). Finally, a qualitative exploration of SEO implementation with 31 nonprofit executive directors provides context for the operationalization of SEO within human service nonprofits. Results: Chapter 1 provides an overview SEO, including key literature and theory, before introducing the research questions. In chapter 2, the SEO Scale is found to consist of social innovation (including product, process, and and socially transformative social innovations), risk-taking, proactiveness (including planning and forecasting), and market engagement). Chapter 3 outlines a multivariate analysis where the SEO Scale was found to significantly predict the Social Work Management Competencies Scale (including executive leadership, resource management, strategic management, and community collaboration). Chapter 4 presents a qualitative follow-up study with 31 executive directors that focused on the organizational implementation of social entrepreneurship using the empirically validated SEO Scale described in earlier chapters. Finally, chapter 5 identifies common themes from research presented in chapters 2 through 4, and provides a discussion and application of findings. Conslusion: Together, this dissertation provides a cohesive body of work on nonprofit SEO that can be used to inform highly impactful social work management in the human services.
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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 | 0.029 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.035 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".