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Record W2952324435 · doi:10.22215/etd/2016-11541

The Conceptual Representation of Science and Implications for Psychology's Status as a Scientific Discipline

2016· dissertation· en· W2952324435 on OpenAlexaff
Gina Hernandez Coronel

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicAcademic and Historical Perspectives in Psychology
Canadian institutionsCarleton University
Fundersnot available
KeywordsSkepticismCategorizationPerceptionPsychologyNatural scienceEpistemologyRepresentation (politics)Behavioural sciencesNatural (archaeology)Philosophy of scienceEvolutionary psychologyCognitive scienceSocial psychologySocial scienceSociologyPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Research has shown that people are skeptical of psychology's status as a science (Lilienfeld, 2011).The current research aimed to determine whether skepticism towards psychology is rooted in the way people process categorical information.This was achieved by investigating the category science using the family resemblance approach.The results of two experiments showed that chemistry, physics, engineering, and neurology were conceptually the most typical sciences.Unexpectedly, psychology's typicality scores were found to be close to those of these disciplines.Nonetheless, people's representation of science showed a clear distinction between the natural and the social sciences.Psychology did not elicit the characteristic features of the more typical sciences (i.e., the natural sciences).These results may indicate that categorization behavior is the cognitive mechanism responsible for the perception that psychology is unscientific.The possibility that people use stereotypes rather than deliberate consideration of the scientific method to make judgments about science is discussed.

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)0.017
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.041
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0030.037
Scholarly communication0.0100.009
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.051
GPT teacher head0.474
Teacher spread0.422 · 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
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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