Ladders and stairs: how the intervention ladder focuses blame on individuals and obscures systemic failings and interventions
Bibliographic record
Abstract
Introduced in 2007 by the Nuffield Council on Bioethics, the intervention ladder has become an influential tool in bioethics and public health policy for weighing the justification for interventions and for weighing considerations of intrusiveness and proportionality. However, while such considerations are critical, in its focus on these factors, the ladder overemphasises the role of personal responsibility and the importance of individual behaviour change in public health interventions. Through a study of vaccine hesitancy and vaccine mandates among healthcare workers, this paper investigates how the ladder obscures systemic factors such as the social determinants of health. In overlooking these factors, potentially effective interventions are left off the table and the intervention ladder serves to divert attention away from key issues in public health. This paper, therefore, proposes a replacement for the intervention ladder-the intervention stairway. By broadening the intervention ladder to include systemic factors, the stairway ensures relevant interventions are not neglected merely due to the framing of the issue. Moreover, it more accurately captures factors influencing individual health as well as allocations of responsibility for improving these factors.
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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 | 0.038 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.008 | 0.088 |
| Scholarly communication | 0.014 | 0.027 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".