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The understanding of social effects in pain

2018· book· en· W2894992313 on OpenAlexaboutno aff
Amanda C de C Williams

Bibliographic record

VenueOxford University Press eBooks · 2018
Typebook
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsEmpathyPsychologyImitationMechanism (biology)HyperalgesiaNeuroscienceProsocial behaviorCognitive psychologyDevelopmental psychologySocial psychologyMedicineNociceptionInternal medicine

Abstract

fetched live from OpenAlex

The landmark paper discussed in this chapter is ‘Social modulation of pain as evidence for empathy in mice’, published in 2006 by Langford et al. in Mogil’s lab at McGill University, Montreal. It elegantly demonstrated (1) that mice observed and responded to one another’s pain—effectively, socially mediated hyperalgesia; (2) that this was modulated by the nature of the social relationship, occurring between cagemates but not strangers; (3) that the mechanism in the observing mouse involved central sensitization, not local effects. The interactive behaviour met requirements for empathic responding; neither imitation nor emotional contagion could account for these effects. The findings have implications for lab pain research using rodents, for understanding of empathic responses in animals, and for understanding animal social behaviour more widely.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0110.004

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 head0.049
GPT teacher head0.274
Teacher spread0.225 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

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