Haunted Care: Engaging Health Hauntology to Understand Health Citizenship in Evolving Welfare States
Bibliographic record
Abstract
ABSTRACT This paper applies a hauntological framework to explore how health citizenship in the UK is shaped by the spectral presence of neoliberal policies, particularly through increased use of Public‐Private Partnerships (PPPs) in the United Kingdom's National Health Service (NHS). The NHS is considered a keystone of national identity in the UK on account of its core socialist and humanitarian principles. However, decades of neoliberal policies, and particularly the growing implementation of PPPs, have created increased dissonance between the NHS as ideation and the NHS as a material, place‐based health service. I explore how these changes manifest in my father's experiences of a Continuous Glucose Monitor (CGM), considering the spectral significance of the systemic relationships, care pathways, collective imaginaries, and vital functions that are folded into this object, and by extension my father's health citizenship. Assembling hauntological concepts and healthcare experiences, I explore how the CGM mediates between life, care, and industry to illuminate evolving forms of health citizenship in contemporary welfare health systems.
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.067 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".