Bibliographic record
Abstract
Purpose Ideas of health-related deservingness in theory and practise have largely been attached to humanitarian notions of compassion and care for vulnerable persons, in contrast to rights-based approaches involving a moral-legal obligation to care based on universal citizenship principles. This paper aims to provide an alternative to these frames, seeking to explore ideas of a human rights-based deservingness framework to understand health care access and entitlement amongst precarious status persons in Canada. Design/methodology/approach Drawing from theoretical conceptualizations of deservingness, this paper aims to bring deservingness frameworks into the language of human rights discourses as these ideas relate to inequalities based on noncitizenship. Findings Deservingness frameworks have been used in public discourses to both perpetuate and diminish health-related inequalities around access and entitlement. Although, movements based on human rights have the potential to be co-opted and used to re-frame precarious status migrants as “undeserving”, movements driven by frames of human rights-based deservingness can subvert these dominant, negative discourses. Originality/value To date, deservingness theory has primarily been used to speak to issues relating to deservingness to welfare services. In relation to deservingness and precarious status migrants, much of the literature focuses on humanitarian notions of the “deserving” migrant. Health-related deservingness based on human rights has been under-theorized in the literature and the authors can learn from activist movements, precarious status migrants and health care providers that have taken on this approach to mobilize for rights based on being “human”.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.145 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".