I Can But I Shall Not Always Be Empathic
Bibliographic record
Abstract
Empathy, a core process for social interactions, is the capacity to understand and share others' mental states and emotions. Each individual is thought to have a maximum level of empathy (empathic ability) and a spontaneous tendency to express it (empathic propensity), which can be affected by multiple factors. Two within-subject studies were conducted to assess the malleability of empathy by modulating contextual factors and measuring their interaction with psychological characteristics. In Study 1, 59 healthy adults evaluated their empathy for people showing facial expressions of pain following different instructions: Passive Observation and Instruction to Actively Empathize. In Study 2, 56 healthy adults performed a similar task under two conditions: Passive Observation and Observation under a Cognitive Load. The results revealed that empathy was significantly increased in the actively empathizing condition (Study 1) and under a cognitive load, but more importantly for men (Study 2). The level of change between the two conditions was associated with self-reported empathy, autistic, alexithymia and psychopathic traits (Study 1), as well as with working memory capacities and the level of empathy reported in the passive observation condition (Study 2). These findings suggest that an instruction to actively empathize and, surprisingly, a cognitive load can both increase empathy, but not for the same individuals. An instruction to actively empathize seems to increase empathy for individuals with good empathic dispositions, while a cognitive load enhances empathy in people for which empathic propensity is sub-optimal.
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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.009 |
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".