Bibliographic record
Abstract
Community economic development (CED) appeals to both the left and right wing of the political spectrum for different reasons. While some might find this to be a strength of the movement, it will be argued in this thesis that this may not be the case. CED can be all things to all people. Without some form of ideological analysis, the CED movement risks being co-opted by the right wing status quo forces of our society and fails to be a progressive source of change to address structural issues of inequality and oppression. This thesis develops a CED ideological model that can be used as a lens to inform both CED theory and practice. Case studies of SEED Winnipeg, the Assiniboine Credit Union and the People’s Cooperative will be used to illustrate the potential application of the CED ideological model. A discussion of the definition of CED is initially presented followed by an outline of the analytical tools that are used to develop the CED ideological model and to guide the case studies. This includes an examination of the extent to which a CED approach embraces gap filling or transformative objectives. The construction of the proposed CED ideological model based on class, market and state theory perspectives is reviewed. A modified version of the George and Wilding (1996) ideological framework is utilized including the perspectives of anti-collectivists, reluctant collectivists and collectivists. Feminist, anti-racist and anti-colonial perspectives of the CED ideological model are presented as other key elements that need to be examined within the ideological analysis model. The theory, strategies and impact measurements of CED that informs the proposed ideological analysis is further examined with respect to each of the respective CED organizations involved in the case studies. The thesis concludes with a discussion about the importance for the CED movement to have concrete tools to better analyze the role and impact of ideology on CED theory and practice.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".