Understanding constraints and enabling factors to develop tools and resources for non-profit and mission-based organizations
Bibliographic record
Abstract
Increasing and enhancing community assets is seen as a possible solution to alleviate the affordability challenge in the Vancouver Metropolitan Region. To this end Vancity Community Foundation (VCF) and other organizations are seeking ways to support the non-profit sector to redevelop their community owned real estate - that is property owned by and for the benefit of the community. The goal of this research was to outline which factors support or challenge non-profit and mission-based organizations in redeveloping their properties. Redevelopment in this context means to pursue new construction on land that has a pre-existing use with the goal of adding more uses for the benefit of the community. Recommendations are based on findings of interviews conducted with eleven non-profit and mission-based organizations who own properties and have begun a redevelopment process. The study identified common enablers that are necessary for organizations to move forward with redevelopment. These are: · leadership capacity within organizations with respect to the board and champions for redevelopment, · access to professional expertise at all stages of the process, particularly through trustful relationships, · early and collaborative partnership development and · clarifying the vision for a redevelopment project to motivate action internally and externally. As a result of the research, I recommend that VCF develop tools, resources or processes which [firstly] support organizations in developing a vision for their real estate; [secondly] assess their capacity for redevelopment; and [thirdly], facilitate the access to professional external real estate expertise, as well as potential partnerships for redevelopment. The suggested support mechanisms have the ability to particularly address needs of organizations who already have the organizational capacity to oversee a property redevelopment. Additional research is needed with regards to organizations who own underbuilt real estate or hold land, but choose to sell it on the open market.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".