Bibliographic record
Abstract
My dissertation research is interdisciplinary in nature, at the nexus of three areas of scholarly work and actual practices: union renewal and non-unionized workers-rights organizing in Canada and the US; feminist, anti-racist Marxian approaches to class relations as being racialized, gendered and bureaucratic; and, the institutional ethnographic method of inquiry into social reality. My empirical focus is on the Ontario Minimum Wage Campaign (OMWC).\nThe OMWC was a Toronto-based labour-community project to raise the minimum wage to $10 per hour. It was started in 2001 by Justice for Workers (J4W), was carried on by the Ontario Needs a Raise coalition (ONR) from 2003 to 2006, and was re-launched in 2007 by the Toronto and York Region Labour Council (TYRLC) in association with some community groups. The OMWC brought together across time and space activist groups, community agencies and labour organizations, all of whose volunteers, members, clients, educators, officials and staff were the agents and/or targets of the campaign. \nThe apparent victory of the OMWC is quite contested. Local campaign realities were compartmentalized in numerous ways and OMWC involvement met different institutionally specific and coordinated needs. And while coalitions generally arise as vehicles to transcend such institutional separation, the campaign was challenged to materially bridge such compartmentalization. The fragmentation of reality amongst institutions and how it was managed in practice affected how collaboration, participation, and decision-making happened and appeared to have happened in organizing and educational activities. While there were at times transformative intentions, there was generally a pragmatic anti-racist organizing practice and effect.\nI contend that the complexity of contemporary society poses great challenges for the possibilities for human-agency based labour-community workers-rights organizing with a broad-based, political capacity for movement building orientation. I suggest that this is largely so because the social coordination of what we do and what we understand about what we do turns on at least three components of social reality: an institution-based organization of multi-layered social relations that is generally locally circumscribed but extralocally driven; a conditioned individually-driven orientation to meeting human needs; and an ideological orientation to both the content of ideas and thought, and the process of that reasoning.
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 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.035 | 0.021 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".