Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Emerging research suggests that perceptions of injustice after musculoskeletal injury can have a significant impact on a number of pain-related outcomes. AIMS: The purpose of this paper is to review evidence linking perceptions of injustice to adverse pain outcomes. For the purposes of this paper, perceived injustice is defined as an appraisal cognition comprising elements of the severity of loss consequent to injury ("Most people don't understand how severe my condition is"), blame ("I am suffering because of someone else's negligence"), a sense of unfairness ("It all seems so unfair"), and irreparability of loss ("My life will never be the same"). RESULTS: Cross-sectional studies show that high scores on perceptions of injustice are correlated with pain catastrophizing, fear of movement, and depression. Prospective studies show that high scores on perceived injustice are a prognostic indicator of poor rehabilitation outcomes and prolonged work disability. Research shows that perceptions of injustice interfere not only with physical recovery after injury, but perceptions of injustice also impact negatively on recovery of the mental health problems that might arise subsequent to traumatic injury. Although research has yet to address the process by which perceptions of injustice impact on pain-related outcomes systematically; possible mechanisms include attentional disengagement difficulties, emotional distress, maladaptive coping, heightened displays of pain behavior, anger, and revenge motives. CONCLUSIONS: Perceived injustice appears to be associated with problematic health and mental health recovery trajectories after the onset of a pain condition. Future directions for research and treatment are addressed.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it