Bibliographic record
Abstract
Lone Mothers: Building Social Inclusion was a Canada-wide research program funded by the Social Sciences and Humanities Research Council of Canada.The five-year-long study investigated the experiences of lone mothers on social assistance as they coped with newly introduced workfor-welfare requirements amid a changing labour market characterized by growing precarious employment.One of several spin-off projects saw the development of a pilot project for a group of 12-15 lone mothers who were brought together with a skilled facilitator to explore and develop their own competencies and expand their sense of agency.This project was generously funded by the Ontario Trillium Foundation and sponsored by Opportunity for Advancement (OFA), a highly progressive Toronto-based NGO that works with lowincome women.Over a two-year period the group developed into a selfhelp/mutual support group that became very important in the lives of the women participants.Joanne Green and Anne Rattray of OFA, Maria Liegghio and Judit Alcalde, who in turn facilitated the group, and MP Olivia Chow, who gave of her time to talk about organizing for change, were all important mentors for group members. 1 The women in the group were (and are) critical supports for each other.Their names should be on the cover of this volume, and it is one more injustice in their lives that, after much discussion, all of the contributors felt the need to write under a pseudonym to protect themselves and their families.All of us who were fortunate to have had the opportunity to learn from the women of the Trillium group hope that this sharing of their stories will enable the readers of this volume to come to know these women, albeit in a
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.322 | 0.169 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".