Bibliographic record
Abstract
This article argues that the traditional debates between the expressive and compensatory views of tort law ignore the way in which an injury may itself have an expressive component, one that in turn increases the extent of physical harm suffered by a victim. I take up the example of informed consent in the medical malpractice context to show how an excessively narrow idea of physical harm has negative consequences for tort law in general. In these situations, when a physician performs a procedure without providing the patient with sufficient information, we can better understand the harm that occurs through a combination of civil recourse theory and new insights from the field of narrative medicine. Under the current regime, the effort to cabin potential liability for physicians’ well-intended conduct has resulted in a disconnect between a negligence standard—with its requirement of strictly physical injury—and the actual harm in question, which has historically been recognized as at least partially dignitary. I argue that this disconnect can be resolved through a broader view of the nature of the injury suffered when a physician performs an inadequately authorized procedure. A more appropriate view would take into account the newly understood, long-term physical harms that arise when a physician co-opts a patient’s subjective knowledge about and narrative control over his body. I then argue that by focusing on remedies that consider the relational quality of the injury imposed on patients in these cases, tort scholars can be more responsive to actual harms, not only in the case of informed consent but also throughout the tort regime generally.
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 | 0.075 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.083 |
| Scholarly communication | 0.012 | 0.029 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.034 | 0.027 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".