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Commentary on “Toward a Neuroscience of Empathy: Integrating Affective and Cognitive Perspectives”

2007· article· en· W2120943974 on OpenAlexaff
Lucy Biven, Jaak Panksepp

Bibliographic record

VenueNeuropsychoanalysis · 2007
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsEmpathyCognitive neurosciencePsychologyCognitionCognitive scienceNeuroscienceAffective neuroscienceCognitive psychologySocial psychology

Abstract

fetched live from OpenAlex

Nell, V. (2006). Cruelty’s rewards: The gratifications of perpetrators and spectators. Behavioral and Brain Sciences, 25: 211–224. Nishitani, N., Avikainen, S., & Hari, R. (2004). Abnormal imitation-related cortical activation sequences in Asperger’s syndrome. Annals of Neurology, 55: 558–562. Numan, M., & Insel, T. R. (2003). The Neurobiology of Parental Behavior. New York: Springer-Verlag. Panksepp, J. (1998a). Affective Neuroscience: The Foundations of Human and Animal Emotions. New York: Oxford University Press. Panksepp, J. (1998b). A critical analysis of ADHD, psychostimulants, and intolerance of childhood playfulness: A tragedy in the making? Current Directions in Psychological Sciences, 7: 91–97. Panksepp, J. (2001). The long-term psychobiological consequences of infant emotions: Prescriptions for the 21st century. Neuro-Psychoanalysis, 3: 140–178. Panksepp, J. (2002). The MacLean legacy and some modern trends in emotion research. In: G. A. Cory, Jr., & R. Gardner, Jr. (Eds.), The Evolutionary Neuroethology of Paul MacLean. Westport, CT: Praeger, pp. ix–xxvii. Panksepp, J. (2003). At the interface between the affective, behavioral and cognitive neurosciences: Decoding the emotional feelings of the brain. Brain and Cognition, 52: 4– 14. Panksepp, J. (2004). Altruism and helping behaviors: Neurobiology. In: Encyclopedia of Neuroscience (3rd edition), ed. G. Adelman & B. H. Smith. New York: Elsevier. Panksepp, J. (in press). Criteria for basic emotions: Is DISGUST a primary “emotion”? Cognition and Emotion. Panksepp, J., Gordon, N., & Burgdorf, J. (2002). Empathy and the action-perception resonance of basic social-emotional systems of the brain. Behavioral and Brain Sciences, 25: 43–44. Preston, S. D., & de Waal, B. M. (2002). Empathy: Its ultimate and proximate bases. Behavioral and Brain Sciences, 25: 1–72. Raine, A., & Yang, Y. (2006). Neural foundations to moral reasoning and antisocial behavior. Social, Cognitive and Affective Neuroscience, 1: 203–213. Shewmon, D. A., Holms, D. A., & Byrne, P. A. (1999). Consciousness in congenitally decorticate children: Developmental vegetative state as self-fulfilling prophecy. Developmental Medicine and Child Neurology, 41, 364–374. Swain, J. E., Lorberbaum, J. P., Kose, S., & Strathearn, L. (2007). Brain basis of early parent–infant interactions: Psychology, physiology, and in vivo functional neuroimaging studies. Journal of Child Psychology and Psychiatry, 48: 262–287. Toronchuk, J. A., & Ellis, G. F. (in press.). Disgust: Sensory affect or primary emotional system? Cognition and Emotion.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.053
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.038
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.002
Science and technology studies0.0050.010
Scholarly communication0.0060.011
Open science0.0090.004
Research integrity0.0530.073
Insufficient payload (model declined to judge)0.0080.009

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.

Opus teacher head0.017
GPT teacher head0.316
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations18
Published2007
Admission routes1
Has abstractyes

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