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Investigating Object Orientation Effects Across 18 Languages
Sau-Chin Chen, Erin Michelle Buchanan, Zoltán Kekecs, Jeremy K. Miller, Anna Szabelska, Balázs Aczél, Pablo Bernabeu, Patrick S. Forscher, Attila Szuts, Zahir Vally, Ali H. Al‐Hoorie, Mai Helmy, Caio Santos Alves da Silva, Luana Oliveira da Silva, Yago Luksevicius Moraes, Rafael Ming Chi Santos Hsu, Anthonieta Looman Mafra, Jaroslava Varella Valentová, Marco Antônio Corrêa Varella, Barnaby Dixson, Kim Peters, Niklas K. Steffens, Omid Ghasemi, Andrew Roberts, Robert M. Ross, Ian D. Stephen, Marina Milyavskaya, Kelly Wang, Kaitlyn M. Werner, Dawn Liu Holford, Miroslav Sirota, Thomas Rhys Evans, Dermot Lynott, Bethany M. Lane, Danny Riis, Glenn Patrick Williams, Chrystalle B. Y. Tan, Alicia Foo, Steve M. J. Janssen, Nwadiogo Chisom Arinze, Izuchukwu L. G. Ndukaihe, David Moreau, Brianna Jurosic, Brynna Leach, Savannah C Lewis, Peter Robert Mallik, Kathleen Schmidt, William J. Chopik, Leigh Ann Vaughn, Manyu Li, Carmel Levitan, Daniel Storage, Carlota Batres, Janina Enachescu, Jerome Olsen, Martin Voracek, Claus Lamm, Ekaterina Pronizius, Tilli Ripp, Jan Philipp Röer, Roxane Schnepper, Μαριέττα Παπαδάτου-Παστού, Aviv Mokady, Niv Reggev, Priyanka Chandel, Pratibha Kujur, Babita Pande, Arti Parganiha, Noorshama Parveen, Sraddha Pradhan, Margaret Messiah Singh, Max Korbmacher, Jonas R. Kunst, Christian K. Tamnes, Frederike S. Woelfert, Kristoffer Klevjer, Sarah E. Martiny, Gerit Pfuhl, Sylwia Adamus, Krystian Barzykowski, Katarzyna Filip, Patrícia Arriaga, Vasilije Gvozdenović, Vanja Ković, Fei Gao, Lisa Li, Jozef Bavoľár, Monika Hricová, Pavol Kačmár, Matúš Adamkovič, Peter Babinčák, Gabriel Baník, Ivan Ropovik, Danilo Zambrano, Sara Álvarez Solas, Harry Manley, Panita Suavansri, Chun‐Chia Kung, Asil Ali Özdoğru, Çağlar Solak, Sinem Söylemez, Sami Çoksan, İlker Dalḡar, Mahmoud Medhat Elsherif, М В Васильева, Vinka Mlakic, Elisabeth Oberzaucher, Stefan Stieger, Selina Volsa, Janis Zickfeld, Christopher R. Chartier
Bibliographic record
Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsCarleton University
Fundersnot available
KeywordsSentenceMental rotationOrientation (vector space)Mental representationComprehensionObject (grammar)Cognitive psychologyComputer scienceRepresentation (politics)Matching (statistics)Natural language processingTask (project management)PsychologyArtificial intelligenceObject-orientationLinguisticsCognitionObject-oriented programmingMathematicsProgramming languageGeometry
Abstract
OpenAlex records an abstract for this work, but it could not be fetched just now.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.601
Threshold uncertainty score1.000
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 head0.046
GPT teacher head0.387
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
Study designObservational
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
Published2023
Admission routes1
Has abstractyes