Bibliographic record
Abstract
Abstract This book uses an anarchist perspective with a focus on unpacking theory and a discussion of the implications for social work practice. As climate change, the brutality of austerity politics under neoliberal capitalism, xenophobia, and a rising right-wing fascism are increasingly making our lives, and those we intend to help, more difficult, protests against police, power, and authority have resulted in the public imaginary being confronted with images of temporary autonomous zones. The economic uncertainty brought about by the global pandemic, has raised questions about the meaning of “essential worker” and illustrated how capitalism is more interested in commerce than human beings. Grassroots movements, such as Black Lives Matter and Idle no More, are challenging how we think about society, and topics like anarchism have entered the mainstream discourse. Specific topics of social work practice and theory are explored, and anarchist ideas are considered. The reader is encouraged to join in thinking about what such a form of social work practice could be. This book will engage with environmental social work, notions of mental health and recovery that shape ongoing practice, and ideas related to theories of welfare. The argument is being made that anarchist ideas can help us think beyond the hegemony of the state for the collective benefit of all. Furthermore, this book is clear about the assumption that all structural forces are supported by white supremacy in our North American political climate and that anarchist perspectives seek to dismantle these for our collective, mutual benefit.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.061 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".