Bibliographic record
Abstract
Struggles for Justice in Canada and Mexico examines Canadian and Mexican communities engaged in collective action to address problems related to the context of aggressive capitalism, which favours economic freedom of the powerful over the needs of people and the planet. The book’s several case examples portray income-generating projects; action to promote health, adequate housing, and a safe environment (including resistance to mining); women’s resource and advocacy programs; as well as grassroots support organizations and independent organizers. The author gathered stories in six states in the south of Mexico and two provinces in Canada between 2004 and 2010, with follow-up to 2012. Thematically, they centre on oppression and struggles for rights experienced by the poor, women, and Indigenous peoples. The author’s case-study method bolsters her narratives by including interviews, observation, and some participant-observation, with analysis that draws on social movement theory from sociology and community organizing theory from social work as well as knowledge from social psychology, liberation theology, popular education, and political science. The book presents the common themes and illustrates the central theories for practitioners in the many fields that promote social justice: social work, social development, health, human rights, environmental protection, and faith-based justice movements, among others. The conclusion presents a framework for conceptualizing social justice practice as a congruent paradigm composed of values, theory, objectives, and practice methods.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.038 | 0.013 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| 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; 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".