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Record W2141260421 · doi:10.1186/1744-8603-10-27

Challenges faced by multidisplinary new investigators on addressing grand challenges in global health

2014· article· en· W2141260421 on OpenAlexafffundabout
Carmen H. Logie, Helen Dimaras, Anny Fortin, Santiago Ramón‐García

Bibliographic record

VenueGlobalization and Health · 2014
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsMcGill UniversityUniversity of TorontoSickKids FoundationUniversity of British ColumbiaHospital for Sick ChildrenWomen's College Hospital
FundersGrand Challenges CanadaBill and Melinda Gates Foundation
KeywordsGrand ChallengesCommercializationTransformative learningEngineering ethicsSociologyCognitive reframingThematic analysisMentorshipPublic relationsMultidisciplinary approachVisionGlobal healthPolitical scienceHealth careMedicineQualitative researchSocial sciencePsychologyMedical educationEngineeringPedagogy

Abstract

fetched live from OpenAlex

BACKGROUND: The grand challenges approach aims to spark innovative and transformative strategies to overcome barriers to significant global health issues. Grand Challenges Canada endorses an 'Integrated Innovation™' approach that focuses on the intersection of scientific/technological, social and business innovation. In this article we explore themes emerging from a dialogue between the authors, who are multidisciplinary recipients of the 'Rising Stars in Global Health' award from Grand Challenges Canada, regarding benefits of engaging in integrated innovation research, and recommendations for how this approach may develop in the future. DISCUSSION: Our dialogue followed a semi-structured interview format that addressed three topics: 1) reflections on applying an Integrated Innovation™ approach for global health; 2) thoughts on participation in the Grand Challenges 2012 meeting; and 3) authors' visions of Grand Challenges Canada and the Grand Challenge movement towards 2020. The dialogue was transcribed verbatim and we used thematic analysis techniques to identify, analyze and report themes in the data. Benefits of working using the Grand Challenges approach centered on two themes: a) the potential for scientific breakthrough and b) building interdisciplinary collaborations and a community of scholars. Challenges and opportunities for Grand Challenges in moving forward included: a) capacity building, particularly regarding Integrated Innovation™ and scale-up planning; b) interdisciplinary and international mentorship for new investigators; and c) potential for future commercialization. CONCLUSIONS: Our discussion highlighted that Integrated Innovation™ offers the opportunity to develop new theories, methods and approaches to global health while simultaneously fostering a collaborative spirit grounded in international, interdisciplinary collaborations. However, the arguable over-emphasis on corporatization poses a major challenge for new investigators. We propose a more balanced way forward that can harness technology to foster mentorship across time and space to support the development of such skills and ideas among new investigators.

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)0.001
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: none
Teacher disagreement score0.796
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.126
GPT teacher head0.397
Teacher spread0.271 · 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".

Quick stats

Citations5
Published2014
Admission routes3
Has abstractyes

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