Bibliographic record
Abstract
Marilyn Waring is a farmer, university lecturer, development consultant, and writer. She is an important voice challenging mainstream economic and political ideologies currently driving globalization. Her best-known work, If Women Counted, describes how economic orthodoxies exclude most of women's productive and reproductive work, rendering half of the world's population invisible. This book is now available from the University of Toronto Press under its original title, Counting for Nothing, and is the subject of a full-length documentary film, Who's Counting? produced by the National Film Board of Canada and released in 1995. Waring argues passionately, powerfully, and convincingly for the urgency of rethinking basic economic concepts such as gross domestic product in ways that take community well being into account. In her latest publication, Three Masquerades (Auckland University Press, 1996), Waring explores the interconnections between equality, work, and human rights. Until the whole is exposed to question, Waring warns, nothing alters in the power dynamics of who chooses, who judges, who defines, who rules, who imposes... and lies masquerade as truths.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.010 |
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".