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Imagining and Imaging the Social Brain: The Case of Mirror Neurons

2016· article· en· W2530696209 on OpenAlexvenueno aff
Susan Lanzoni

Bibliographic record

VenueCanadian Journal of Health History · 2016
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsnot available
Fundersnot available
KeywordsEmpathyMirror neuronSocial neuroscienceImitationEmbodied cognitionPsychologyCognitive scienceCultural neuroscienceSocial cognitionTheory of mindCognitive neuroscienceNeuroscienceCognitionCognitive psychologyEpistemologySocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

In a contemporary setting in which all things “neuro” have great cultural sway, an analysis of the ways in which neuroscience is indebted to the methods and findings of the social sciences has received less attention. Indeed, in the new specialization of social neuroscience, neuroscientists now collaborate with contemporary psychologists and invoke historical psychological theories to help theorize empathy and social understanding. This article examines the overlap between psychological frameworks of social emotion and neuroscience in the case of mirror neurons, discovered in the 1990s. Some neuroscientists purport that mirror neurons underlie the social behaviours of imitation and empathy, and have found support for this view of theories of simulation and embodied cognition. They have also invoked pragmatic and phenomenological approaches to mind and behaviour dating back to the early 20 th century. Neuroscientists have thus imported, adapted, and interpreted psychological models to help define social understanding, empathy, and imitation in many imaging studies.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.781
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.064
GPT teacher head0.330
Teacher spread0.266 · 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 teacher head, not a consensus.

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

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

Citations2
Published2016
Admission routes1
Has abstractyes

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