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36 DECOLONIZING EXHIBITIONS AND PUBLIC COGNITION: BEHAVIORAL AND COGNITIVE SCIENCE PERSPECTIVES ON THE MONTREAL MUSEUM OF ARCHAEOLOGY AND HISTORY

2025· article· en· W4417229701 on OpenAlexaffabout
Qi Dang, Jinsong Ye

Bibliographic record

VenueCurrent Opinion in Psychiatry · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsCarleton University
Fundersnot available
KeywordsExhibitionCognitionHistory of sciencePublic history

Abstract

fetched live from OpenAlex

Introduction: Decolonizing public history has become a critical focus for museums, particularly in postcolonial societies like Canada. Traditional exhibitions often marginalize Indigenous perspectives, reinforcing colonial schemas and limiting collective cognitive and emotional engagement. Integrating behavioral and cognitive science into museum design offers the potential to reshape public cognition, empathy, and collective memory, with implications for cultural psychiatry and social well-being. By examining exhibitions as structured cognitive environments, this study situates museums at the intersection of education, psychology, and cultural healing. It emphasizes that decolonization is not solely a curatorial act of inclusion but a process of cognitive restructuring and emotional reconciliation that challenges entrenched historical frameworks. Methods: This study examines the Montreal Museum of Archaeology and History (Pointe-à-Callière) as a representative case for decolonizing exhibition strategies. The analysis draws on principles from cognitive psychology, behavioral science and embodied cognition to evaluate exhibition design, visitor flow, multisensory engagement, and narrative integration. Qualitative evidence is synthesized from visitor studies, architectural and curatorial documentation, and interdisciplinary theoretical frameworks. Special attention is given to the ways in which spatial sequencing, affective cues, and participatory design act as behavioral interventions that foster empathy, reflection, and schema reconstruction. Results: Findings indicate that strategically sequenced exhibitions, multisensory experiences, and co-curated Indigenous narratives effectively engage visitors’ attention, promote schema reconstruction, and stimulate empathy and moral reasoning. Behavioral interventions—such as spatial hierarchy, lighting, and interactive displays—guide cognitive and emotional processing, while narrative coherence enhances moral reflection. Visitors’ engagement with decolonized narratives produces enhanced memory retention, perspective-taking, and reflective understanding of historical trauma. Moreover, the museum's spatial rhythm and emotional allowing visitors to confront difficult histories in a psychologically contained and meaningful way. The museum thus functions as a cognitive-emotional environment that facilitates both individual and collective reappraisal of historical knowledge. Conclusions: Decolonizing exhibitions that integrate behavioral and cognitive science principles can serve as non-clinical interventions for cultural and collective mental health. By promoting cognitive flexibility, empathy, and reflective engagement, museums become active agents in reshaping public cognition and facilitating collective processing of historical trauma. These findings highlight the potential for museums to contribute to social reconciliation, intergroup understanding, and preventive mental health in postcolonial contexts. The study underscores that museum environments, when informed by behavioral and cognitive insights, can operate as laboratories for empathy and cultural transformation, redefining the museum's role as both an educational and therapeutic public space.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.069
GPT teacher head0.337
Teacher spread0.268 · 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 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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