Women, Work, More: Senior Women & Economic Insecurity — with Sheila Block & Jo-Ann Hannah
Bibliographic record
Abstract
For this final episode of Women, Work, More, host Alyha Bardi speaks with Sheila Block, a senior economist from the Canadian Center for Policy Alternatives, and Jo-Ann Hannah, retired Director of the Pensions and Benefits at Unifor, and board member at the BC Financial Services Authority.\n \nSheila and Jo-Ann speak in conversation about retirement incomes with a gender and racial equity lens, and explore how pay gaps and gendered life-patterns influence income security for senior women. They speak to the flaws in existing public and private pension systems, discuss the benefits and downfalls of the Canada Pension Plan (CPP), and explore solutions in the realms of structural changes, public services and healthcare, and pooled retirement pensions systems.\n \nThroughout the episode we hear from four senior women, as they speak about their life-work trajectories, and the resulting money struggles, worries, or “lucks” they have now — while expressing dissatisfaction with lacking assistance from government systems.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.061 | 0.018 |
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".