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Record W1522883374 · doi:10.22230/src.2014v5n1a135

What Kind of Scientist Are You? Science and Interdisciplinary Research

2013· article· en· W1522883374 on OpenAlexaffvenue
Yolanda F. Wiersma

Bibliographic record

VenueScholarly and Research Communication · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicInterdisciplinary Research and Collaboration
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsDisciplineSociologyGovernment (linguistics)HumanitiesPolitical scienceLibrary scienceSocial sciencePhilosophy

Abstract

fetched live from OpenAlex

Scientific research that crosses disciplinary boundaries (“interdisciplinary research”) – and in particular, research that crosses academic boundaries to engage with industry, government and non-government agencies, and the broader public – can be rewarding personally and yield novel approaches and findings. While the scholarly literature suggests that interdisciplinary approaches are of immense value, interdisciplinary research carries challenges to academics, particularly in terms of funding and in relation to finding an academic “home.” In this article, the author outlines what is meant by interdisciplinary research and reflects on her career leading from graduate school to tenure. She illustrates how the interdisciplinary projects she has been involved in have been both rewarding and challenging. While not every scientist must be interdisciplinary, she concludes that being open to such an approach has many advantages.La recherche scientifique qui dépasse les frontières disciplinaires (la recherche « interdisciplinaire ») —et, particulièrement, celle qui dépasse les frontières académiques pour s’engager avec l’industrie, les agences gouvernementales et nongouvernementales et le public—peuvent être personnellement enrichissantes et engendrer de nouvelles approches et résultats. Même si la littérature académique indique que les approches interdisciplinaires ont beaucoup de mérite, la recherche interdisciplinaire pose des défis aux universitaires, notamment par rapport à l’obtention de subventions et la possibilité de trouver un chez-soi académique. Dans cet article, l’auteure décrit ce que l’on entend par recherche interdisciplinaire et réfléchit sur son propre parcours, des études supérieures à la titularisation. Elle montre ainsi comment les projets interdisciplinaires auxquels elle a participé ont été à la fois enrichissants et stimulants pour elle. Elle conclut que, bien que chaque savant ne doive pas être interdisciplinaire, être ouvert à une telle approche a plusieurs avantages.

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)0.081
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Open science
Consensus categoriesMetaresearch, Science and technology studies, Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0810.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0050.009
Scholarly communication0.0150.019
Open science0.0030.010
Research integrity0.0000.002
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 head0.252
GPT teacher head0.539
Teacher spread0.287 · 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; both teacher heads agree on what is shown here.

Study designOther design
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
Published2013
Admission routes2
Has abstractyes

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