Income Assistance in British Columbia: Reforms Along Basic Income Lines
Bibliographic record
Abstract
IA is the Government of British Columbia’s largest income assistance program, with an annual cost of just over $2B and reaching more than 8% of households. It is a program that is very complex to access and has complex eligibility rules and design features. It is also associated with a large amount of stigma and does not foster the financial stability and financial security of its clients. IA is also a poor tool to support those who engage in vital unpaid work (e.g., child care; caregiving for ill, disabled, or elderly family members; volunteering), not only because of the stigma associated with the program but also because the benefit levels are inadequate. The purpose of this paper is to put the IA program through the lens of BI principles to recommend reforms that would move IA closer to BI principles and away from being a “funder of last resort.” Taken together, reforms based on BI principles should make IA a more inclusive program that recognizes the worth of all people. These reforms will also help reduce income poverty rates and poverty depths, preventing poverty, and help those caught in or about to be caught in a poverty trap.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".