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Record W4386303658 · doi:10.3102/ip.23.2005210

A Science Exhibit About Mental Health: Expectations and Engagement Perspectives

2023· article· en· W4386303658 on OpenAlexaff
Ana Maria Navas Iannini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsSimon Fraser University
FundersUniversität Wien
KeywordsMental healthComputer scienceData sciencePsychologyPsychiatry

Abstract

fetched live from OpenAlex

In the last century and a half, scientific development has been breathtaking, but the understanding of this progress has dramatically changed.It is characterized by the transition from the culture of 'science' to the culture of 'research.'Science is certainty; research is uncertainty.Science is supposed to be cold, straight, and detached; research is warm, involving, and risky.Science puts an end to the vagaries of human disputes; research creates controversies.Science produces objectivity by escaping as much as possible from the shackles of ideology, passions, and emotions; research feeds on all of those to render objects of inquiry familiar (Latour 1998, 208-209).How did the transition from "science" to "research" described by sociologist and philosopher of science Bruno Latour materialise in the world of science museums and science exhibitions?This question lies at the heart of this paper.My aim is to examine the changing roles of science exhibitions from places of "cold" science, where secure, closed and fixed knowledge is communicated, to places that increasingly engage with "hot", controversial research and open debates.The examples discussed are European ones (from the United Kingdom, France and, above all, Austria) and I will be focussing on the display of controversies, rather than on displays that cause controversy.In the first part of the paper, I discuss how controversies have been studied in the field of science studies.In the second I examine the recent evolution of (some) museums from "cold" to "hot".Then, in the third part, I look at two recent exhibitions that dealt with the controversial nature of science.I will argue that while the "cold" way to exhibit science is through stabilised objects, the "hot" way works through relationality, that is, through highlighting the multiple relationships between visitors and objects, and between the positions of the various contenders in the controversy.The paper develops the concept of a "texture of controversy" in trying to make sense of exhibition arrangements focused on positions, relationships and processes, rather than stabilised products and objects.In displays about controversies we encounter an object that is open in many ways: to be flexibly interpreted, to be engaged with, to be questioned, to be challenged.Such an object materialises a number of symmetries: between various actors, between art and science, and between right and wrong.Two examples from the city of Vienna -the Gallery of Research and the true/wrong inc.exhibition -will shed some light on how controversial science can be exhibited. The study of controversies in science studiesOne way to make sense of the shift from cold science to hot research comes from the field of science studies (often interchangeably referred to as 'science, technology and society' or 'science and technology studies' or

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)0.026
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.035
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0320.040
Scholarly communication0.0350.019
Open science0.0040.032
Research integrity0.0120.019
Insufficient payload (model declined to judge)0.0070.001

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 head0.227
GPT teacher head0.567
Teacher spread0.340 · 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.

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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