Feminist Visions of the Future of Women’s Work: A systemic exploration of the past, present, and future of women at work in Canada
Bibliographic record
Abstract
We are still far from achieving gender equality at work, as our modern workplace is designed by men for men. Women’s economic participation and prosperity face systemic barriers and are further threatened by the digitization and automation that drive the future of work. These technological advances, along with demographic shifts, social movements, and political factors, lead to new disruptive employment systems. However, the impacts and discussion around the future of work are often gender-blind. \n \nThis research uses a systemic lens to explore the past, present, and future of women’s work. A systemic analysis of gender equality in the workplace reveals how our workplace, governance, social, and economic structures create systemic barriers to undervalue women’s work. Strategic foresight is used to explore the trends shaping the future of work using a gendered lens, and scenarios help us envision how our systems can evolve to value women’s work. Risks and opportunities from each scenario informed insights that can help us design our preferred future, where women can fully participate in the workplace and be valued for their contributions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".