In Praise of Empathy: The Glue that holds Caring Communities Together in a Fractured World
Bibliographic record
Abstract
In a tumultuous world where populism is on the rise as the result of an enraged, disenchanted, misguided and susceptible populace, empathy, one of the most vital of our moral virtues, is in serious jeopardy. Fear, prejudice and the rise of the extreme right has provoked a number of nay-sayers to draw our attention to what they believe to be the darker side of empathy, its biases and its vulnerability to subversion. This paper examines empathy, what it is, how it feels, the neural and environmental basis for its development, our moral obligation to nurture it in our children and how it may be induced in the case of empathy deficiencies. It considers the influences of gender and hormones on the expression of empathy and its relationship with sympathy and compassion. Also discussed are the properties of empathy as a motivational, socioemotional mechanism, that evokes kindness, caring, compassion and understanding in each of us, and its potential to neutralize the negativism, cruelty, violence and aggression, so prevalent in the world today.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.021 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".