The Role Of Volunteer Lawyers In Challenging The Conditions Of A Local Housing Crisis In Buffalo, Ny
Bibliographic record
Abstract
Abstract The organization and delivery of pro bono legal services has become increasingly institutionalized over the last quarter-century in jurisdictions across the United States. During this time, according to Cummings (2004), an intricate network of professional, private commercial and nonprofit, and public-sector legal organizations has emerged and set out to construct a “centralized and streamlined” pro bono system. The implications of organized pro bono’s emergence and institutionalization deserve more nuanced scholarly attention than has been given. Little is known, for instance, about how these changes affect the consciousness and actions of legal practitioners around issues of pro bono service. According to Cummings (2004:6), organized pro bono inculcates a set of “values and practices that have become deeply ingrained as part of the culture of legal professionalism, defining how lawyers understand their role in making legal services available to poor and underrepresented groups.”
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".