Socially Inclusive Parenting Leaves and Parental Benefit Entitlements: Rethinking Care and Work Binaries
Bibliographic record
Abstract
How can parental leave design be more socially inclusive? Should all parents be entitled to parental benefits or only those parents who are eligible based on a particular level of labour market participation? To think through questions of social inclusion in parental leave policy design, particularly issues related to entitlements to benefits, I make three arguments. First, aiming to extend Dobrotić and Blum’s work on entitlements to parental benefits, I argue that ‘mixed systems’ that include both citizenship‐based and employment‐based benefits are just and socially inclusive approaches to parental leaves and citizenship. Second, to build a robust conceptual scaffolding for a ‘mixed’ benefits approach, I argue that that we need to attend to the histories and relationalities of the concepts and conceptual narratives that implicitly or explicitly inform parental leave policies and scholarship. Third, and more broadly, I argue that a metanarrative of care and work binaries underpins most scholarship and public and policy discourses on care work and paid work and on social policies, including parental leave policies. In this article, I outline revisioned conceptual narratives of care and work relationalities, arguing that they can begin to chip away at this metanarrative and that this kind of un‐thinking and rethinking can help us to envi‐ sion parental leave beyond employment policy—as care and work policy. Specifically, I focus on conceptual narratives that combine (1) care and work intra‐connections, (2) ethics of care and justice, and (3) ‘social care,’ ‘caring with,’ transforma‐ tive social protection, and social citizenship. Methodologically and epistemologically, this article is guided by my reading of Margaret Somers’ genealogical and relational approach to concepts, conceptual narratives, and metanarratives, and it is written in a Global North socio‐economic context marked by the COVID‐19 pandemic and 21st century neoliberalism.
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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 | 0.023 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.071 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.004 | 0.008 |
| 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".