Comparing Public Social Provision and Citizenship in the United States, Canada, and Mexico: Are There Implications for a North American Space?
Bibliographic record
Abstract
This study compares the reform of public social provision in the United States, Canada, and Mexico from 1996 to 2006. It highlights important parallels among the three countries in terms of policy design, discourses that frame each policy, and the ways social citizenship has become reconfigured. We argue that in all three cases, poor women/mothers are being regulated, monitored, and held accountable through surveillance and sanctions, reinforcing how social rights have morphed into social responsibilities and obligations. The objective is to shift welfare from “passive” support to “active” integration into the market, reinforcing a worker‐citizen model within precarious labor markets. The Canadian model shares elements with the U.S. model in its emphasis on welfare‐to‐work policies and integrating single mothers with young children into the workforce. The Mexican model integrates mothers as consumers into the market while investing in their children as future worker‐citizens. The article concludes by broadening the discussion from country‐specific analysis to speculating about the possibility of integrating workers within a North American market.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".