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Record W4416087457 · doi:10.1177/20966083251395331

Science museums in a time of crisis: Insights from Brazil, Canada, Finland and Portugal

2025· article· en· W4416087457 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCultures of Science · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMuseum informaticsMuseologyHistory of scienceNational museumCitizen scienceQualitative researchNatural (archaeology)

Abstract

fetched live from OpenAlex

This research examines how science museum teams in different countries addressed crises during the COVID-19 pandemic, and what values, priorities and practices emerged during this challenging time. Informed by theoretical perspectives related to broken world thinking and care, this paper summarizes and discusses findings related to four qualitative case studies: the Museum of Tomorrow (Brazil), the Royal BC Museum (Canada), Heureka the Finnish Science Centre (Finland) and the National Museum of Natural History and Science (Portugal). Data gathered during 2023–2024 centred on the voices and lived experiences of 26 museum professionals, as well as documents and artefacts shared by them. Findings highlight how local realities shaped institutional responses to the pandemic, and how all four institutions nurtured caring relationships, faced uncertainty through reflective attentiveness and became relevant civic and scientific resources in a time of crisis. The research shed light on how care can become a central pathway to guide the transformation of science museums both inwardly and outwardly.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.611
Threshold uncertainty score0.924

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 studies0.0000.003
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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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