Bibliographic record
Abstract
1. Introduction - Scott Harding and Louise Simmons, both at University of Connecticut School of Work Economic Realities, History and Framing 2. Inequality and Its Discontents: The Threatened Middle Class - Jill Littrell, Fred Brooks, Jan Ivery, Mary Ohmer, all of Georgia State University 3. Economic Justice in a Global Context: International Comparisons of Policies that Support Economic Justice - Cynthia Rocha, University of Tennessee, College of Work 4. Workers, Unions and Low Wage Workers: A Historical Perspective - Michael Reisch, University of Maryland School of Work 5. Where's the Freedom in Free Trade? Framing Practices and Global Economic Justice - Loretta Pyles, University of Albany, State University of New York Labor-Community Partnerships for Economic Justice 6. The Politics and Practice of Economic Justice: Community Benefits Agreements as Tactic and Strategy of the New Accountable Development Movement - Virginia Parks, University of Chicago, and Dorian Warren, Columbia University 7. Evolving Strategies of Labor-Community Coalition Building - David Dobbie, Wayne State University 8. Organizing Community and Labor Partnerships for Community Benefits Agreements in African American Communities: Ensuring Successful Coalitions - Bonnie Young Laing, Youngstown State University 9. Critical Pedagogy as a Tool for Labor-Community Coalitions - Roland Zullo & Gregory Pratt, both at University of Michigan On the Front Lines, In the Classrooms 10. Social Justice Infrastructure Organizations as New Actors from the Community: the Case of South Florida - Bruce Nissen, Center for Labor Research and Studies at Florida International University 11. Working Hard, Living Poor: Work and the Movement for Livable Wages - Susan Kerr Chandler, University of Nevada, Reno, School of Work 12. Organizing for Immigrant Rights: Policy Barriers and Community Campaigns - Jill Hanley, School of Work, McGill University and Eric Shragge, School of Community and Public Affairs, Concordia University 13. Outcomes of Two Construction Trades Pre-Apprenticeship Programs: A Comparison - Helena Worthen, University of Illinois School of Labor and Employment Relations and Anthony Haynes, Building Bridges Project, Arise Chicago 14. One Small Revolution: Unionization, Community Practices and Workload in Child Welfare - Tara LaRose, Ryerson University
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.013 | 0.027 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.035 | 0.006 |
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".