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Record W2172232568 · doi:10.1126/science.1185745

Empowering Young Scientists

2010· editorial· en· W2172232568 on OpenAlex
Tilman Brück, Catherine Beaudry, H. Hilgenkamp, Nitsara Karoonuthaisiri, Hiba Salaheldin Mohamed, Gregory A. Weiss

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueScience · 2010
Typeeditorial
Languageen
FieldSocial Sciences
TopicConferences and Exhibitions Management
Canadian institutionsPolytechnique MontréalCenter for Interuniversity Research and Analysis on Organizations
Fundersnot available
KeywordsGlobeHonorPromotion (chess)AthletesIndependence (probability theory)Political scienceWork (physics)Public relationsPsychologySociologyLawMedicinePoliticsEngineeringInternet privacy

Abstract

fetched live from OpenAlex

The Vancouver Olympics reveal stark differences between the worlds of sports and science. In both, young people from around the world try to surpass all previous accomplishments in pursuit of world records or scientific discoveries. Selected entirely on merit, athletes receive honor just for participating in the games, spurring the next generation of young people in each nation to excel. And as star athletes age, they often support their sport in other ways, serving as advocates, mentors, or coaches. In contrast, in too many nations, the selection and promotion processes in science involve considerations other than merit. Senior scientists receive most of the resources available for scientific research, and young scientists rarely receive societal recognition for their work. This situation is growing worse as life expectancies and retirement ages increase, along with the average age for attaining scientific independence. * Perhaps as one consequence, science is typically not a top career choice. How many exceptional scientists around the world thereby go unrecognized, their talents allowed to wither away untapped? In an attempt to reverse such trends, a nascent “young national academies” movement has begun across the globe, and a new international group has recently been established to promote this cause.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.177
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.363
Teacher spread0.350 · 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