Bibliographic record
Abstract
n Total expenditures on legal aid in Canada were $536.1 million in 1996-97, a 14 % decrease from 1995-96. Expressed in per capita terms, legal aid spending dropped to $17.90 per Canadian in 1996-97, compared to $21.00 in 1995-96. This marks the second year in a row that expenditures decreased, ending a period of generally increased expenditures between 1986-87 and 1994-95 (with the exception of 1993-94, when a slight decrease was experienced). n Of the $465.1 million spent on direct legal services in 1996-97, 68 % was paid to private lawyers, and the other 32 % went to salaried professionals. n Governments continue to be the major source of revenue for legal aid plans, contributing 90 % of total revenues. The remainder of the revenue came from client contributions and cost recoveries (4%), legal profession contributions (2%), and other sources (3%). n In 1996-97, there were 824,451 applications submitted for legal aid assistance, a 15 % drop from 1995-96. This is even lower than the 835,270 filed in 1988-89, before the legal aid system experienced higher volumes of applications in the early nineties, with a peak of 1,171,095 applications in 1992-93. n There were also fewer applications approved, totalling 510,914 in 1996-97, 21 % less than the previous year. Approved applications constituted 62 % of total applications received. n The recent declines in approved applications can be largely accounted for in Ontario, where the government has reduced funding. This has resulted in tightened eligibility criteria for legal aid in Ontario. n Although all but two jurisdictions approve more applications for criminal cases than for civil, at the national level, slightly over half of all approved applications (53%) are civil cases. 2 Statistics Canada – Catalogue no. 85-002-XIE, Vol. 18, No. 10 Ordering/Subscription information All prices exclude sales tax Catalogue no. 85-002-XPE, is published in a paper version for $10.00 per issue or $93.00 for an annual subscription in Canada. Outside Canada the cost is
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.140 | 0.022 |
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".