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Record W2220306430 · doi:10.20396/cel.v40i0.8637115

As necessidades da pesquisa experimental em psicolingüística no Brasil

2011· article· en· W2220306430 on OpenAlexaff
Leonor Scliar-Cabral

Bibliographic record

VenueCadernos de Estudos Lingüísticos · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and Education Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPsycholinguisticsPerspective (graphical)Field (mathematics)CurriculumOrder (exchange)Applied linguisticsComputer scienceLinguisticsSociologyPsychologyPedagogyEngineering ethicsArtificial intelligenceEngineeringPhilosophyCognition

Abstract

fetched live from OpenAlex

This paper takes a historical perspective on the state of the art of experimental psycholinguistics in Brazil and attempts to make a diagnosis of the resources needed, both material and human, for the advancement of the field in this country. It is suggested that a comprehensive database on existing research centers and their scientific production be constructed in order to stimulate peer contact and debate. An recommendation is also made for curricula to be designed in such a way graduates in Psychology get the proper linguistics training and graduates in Linguistics get the proper training in experimental design and statistics.

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)0.172
metaresearch head score (Gemma)0.404
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.907

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1720.404
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.007
Science and technology studies0.0070.011
Scholarly communication0.0060.008
Open science0.0040.010
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0120.001

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.

Opus teacher head0.100
GPT teacher head0.323
Teacher spread0.222 · 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.

Study designTheoretical or conceptual
DomainMethods
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

Citations0
Published2011
Admission routes1
Has abstractyes

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