The risks of being a lone mother on income support in Canada and the USA
Bibliographic record
Abstract
Purpose This paper aims to explore how neo‐liberalism shapes income support policy and lone mothers' experiences in Canada and the USA. Design/methodology/approach A critical comparative analysis is undertaken of how Canadian and US governments take up sociological concepts of risk, market citizenship, and individualization, whether explicitly or implicitly, in the design and administration of neo‐liberal income support policies directed at lone mothers. Specifically, the contradictory life circumstances that Canadian and American lone mothers experience when they access income supports that are designed ostensibly to construct/reconstruct them as citizens capable of risk taking in their search for employment and self‐sufficiency are compared. Findings The paper finds that the realities for poor lone mothers are remarkably similar in the two countries and therefore argue that income support policies, particularly welfare‐to‐work initiatives, underpinned by neo‐liberal tenets, can act in a counter‐intuitive manner exposing lone mothers to greater rather than lesser economic and social insecurity/inequality, and constructing them as risk aversive and dependent. Research limitations/implications The economic and social implications/contradictions of neo‐liberal restructuring of income support policies for lone mothers is revealed. Originality/value This paper contributes to broader scholarship on the gendered dimensions of neo‐liberal restructuring of welfare states in late modernity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".