Programmatic vs Process Outcomes for Systemic Change in Cross Sector Social Partnerships. Evidence from the UK context. 5th International Cross Sector Social Interactions (CSSI) Symposium in Toronto, 17-19 April 2016, Toronto, Canada.
Bibliographic record
Abstract
Cross Sector Social Partnerships (CSSP) constitute “social problem solving mechanisms” (Waddock, 1989: 79) that aim to address social issues (Selsky and Parker, 2005) (e.g. education, poverty, health, environment). The collaboration (Gray, 1989; McCann, 1983; Huxham and Macdonald, 1992; Huxham, 1993) and social partnerships literatures (Waddock, 1991; Austin, 2000; Warner and Sulivan, 2004; Selsky and Parker, 2005; Galaskiewicz, and Colman, 2006; Wymer and Samu, 2003) have extensively documented the difficulties in developing partnerships (Teegen et al, 2004; Bryson et al, 2006; Kolk et al, 2008) due to misunderstandings, power imbalances (Berger et. al, 2004; Seitanidi and Ryan, 2007) and occasionally due to the lack of overt functional conflict (Seitanidi, 2010). The literature has identified several factors of what constitutes a successful partnership (Austin, 2000; Googins and Rochlin, 2001; Bryson et al, 2006; Rondinelli & London, 2003; Bouwen & Taillieu, 2004) and suggested stage models that identify key issues that need to be addressed within the different stages of social problem-solving interventions (Mc Cann, 1983; Gray, 1985, Waddock, 1989; Waddell and Brown, 1997; Seitanidi and Crane, 2009). Despite the identification of factors and issues as pre-conditions for successful partnerships the direct study of partnership outcomes is surprisingly a less prominent area of research, particularly within nonprofit-business partnerships (Seitanidi, 2010).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.002 | 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; both teacher heads agree on what is shown here.
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".