Good, Responsible Parenting: Child-Support Guidelines in an Era of Neo-liberalism
Bibliographic record
Abstract
Abstract Following decades of criticism, the federal government amended the Divorce Act in 1997 to include guidelines and support tables for the determination of child-support orders. The guidelines were meant to replace a child-support system that relied heavily on judicial discretion, which was blamed for the inconsistency between awards, the inadequacy of the amounts awarded, and inequity in the system. Normative messages about parental responsibility and good behaviour were reinforced in the new child-support regime. Through an analyses of case law, government documents, and interviews with lawyers, unique insight is gained in expanding our understanding of what is happening “on the ground,” beyond the “black letter of the law,” pursuant to the child-support law reforms. This article outlines the dominant message about responsibility that parents receive when they encounter child-support law. Further, it is necessary to consider the socio-economic context in which these reforms have occurred, as they have significant implications for the family in today's society. In the current climate of neo-liberalism, the reformed child-support legislation might be seen as one strategy in the state's reconfiguration of responsibility for the welfare of children. This research demonstrates that while the rationalization of child support has achieved some key objectives, it will fail as an anti-poverty measure.
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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 | 0.034 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.052 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.009 | 0.012 |
| 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".