Gender-Based Analysis Plus (GBA+) of the Current System of Income and Social Supports in British Columbia
Bibliographic record
Abstract
This paper is one of three papers focused on bringing a GBA+ lens to the work of the Expert Panel on Basic Income. In Cameron and Tedds (2020b), background is provided on gender and intersectional analysis and an enhanced GBA+ framework is developed based on the Status of Women Canada’s GBA+ tool. In Cameron and Tedds (2020a), a GBA+ analysis is applied to two policy reforms—basic income and basic services—to consider their potential in the context of B.C.’s poverty reduction strategy. In this paper, we apply the enhanced GBA+ analysis to the current system of income and social supports in B.C. along with the suite of proposed reforms recommended in Petit and Tedds (2020d, 2020e) using BI principles. Both of these—BI principles and GBA+/intersectionality—have transformative potential. Applying a GBA+ lens along with BI principles illuminates ways we can address structural barriers such as institutional and systemic discrimination, reducing the risk of poverty among diverse groups and promoting long-term transformative change.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".