The Community Being Helped Is the Resource That is Needed
Bibliographic record
Abstract
There is a widespread recognition of the importance of not-for-profit organizations for meeting the access to justice needs of disadvantaged people. Centered within that growing body of literature, this paper points to the importance of community service agencies and voluntary organizations as resources that enable community legal clinics to identify and meet the legal needs and to provide social justice outcomes that would otherwise be beyond their capacity if limited to resources from conventional sources. The resources available from the community are not monetary. They include entrée into hard-to-reach and -serve populations, special knowledge of about the problems experienced by disadvantaged groups and collaborative partnering between trusted intermediaries and community legal clinics to achieve resolutions to problems that make sense to the people experiencing them. Collaborative partnering extends the reach of legal services, building the capacity of community groups and making them part of the ecosystem of access to justice. Illustrations supporting the “community as a resource” hypothesis are drawn from recently documented service delivery innovations developed in several Ontario community legal clinics.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.024 | 0.019 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.045 | 0.014 |
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".