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Record W4401888297 · doi:10.1007/s42087-024-00432-3

The Meandering Course from Psycholinguistics to Cognitive Science and Neuroimaging: The Organization of (Inter-) Disciplinary Research in the History of the Max Planck Institute for Psycholinguistics

2024· article· en· W4401888297 on OpenAlexaff
Frank W. Stahnisch

Bibliographic record

VenueHuman Arenas · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversity of Calgary
FundersMax-Planck-GesellschaftRadboud Universiteit
KeywordsPsycholinguisticsNeurolinguisticsCognitive scienceDisciplineCognitive neurosciencePsychologyCognitionCognitive psychologyNeuroscienceEpistemologySociologyPhilosophySocial science

Abstract

fetched live from OpenAlex

This article is a historical and philosophical exploration of the psycholinguistics work at the Max Planck Institute for Psycholinguistics (MPIPL) from its very beginnings until 2002. Historical archival and interview materials provide useful and important evidence on the meandering course of the research programs at the MPIPL that so tidily mirror the historical changes in the larger field. From the psycholinguistics trajectory of Jerome Bruner (1915–2016) to recent behavioural neuroscience work, pioneered for example by psychiatrist Detlev Ploog (1920–2005), what we can learn from these traditions of psychology is that they harbour potential still not fully harvested by neuroscience. Pim Levelt (b. 1938) and his colleagues at the MPIPL observed these important changes in their research programs over a period of three decades, exemplified by their work on the neural basis of vocalization. In fact, both Levelt and Ploog had for some time been interested in the comparative aspects and differences of corticopyramidal tract instantiations of speech-motor systems while also considering Bruner’s psychological work in regard to this endeavour. Yet, the “switch” to neurolinguistics and neurobehaviourism at the Nijmegen institute occurred only with the late 1990s and early 2000s, fomented especially by collaboration with the Donders Institute at Radboud University in Nijmegen.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.188
GPT teacher head0.434
Teacher spread0.246 · 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 designBench or experimental
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

Citations1
Published2024
Admission routes1
Has abstractyes

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