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Record W2788678121 · doi:10.1186/s12998-018-0173-3

Leadership and capacity building in international chiropractic research: introducing the chiropractic academy for research leadership (CARL)

2018· article· en· W2788678121 on OpenAlexafffundabout
Jon Adams, Greg Kawchuk, Alexander Breen, Diana De Carvalho, Andreas Eklund, Matthew Fernandez, Martha Funabashi, Michelle M. Holmes, Melker S. Johansson, Katie de Luca, Craig Moore, Isabelle Pagé, Katherine A. Pohlman, Michael Swain, Arnold Yu Lok Wong, Jan Hartvigsen

Bibliographic record

VenueChiropractic & Manual Therapies · 2018
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversité du Québec à Trois-RivièresMemorial University of NewfoundlandUniversity of Alberta
FundersSyddansk UniversitetUniversity of Technology SydneyUniversity of AlbertaEuropean Centre for Chiropractic Research ExcellenceNordisk Institut for Kiropraktik og Klinisk Biomekanik
KeywordsChiropracticMentorshipMedicineHealth careMedical educationAlternative medicinePublic relationsManagementPolitical science

Abstract

fetched live from OpenAlex

In an evidence-based health care environment, healthcare professions require a sustainable research culture to remain relevant. At present however, there is not a mature research culture across the chiropractic profession largely due to deficiencies in research capacity and leadership, which may be caused by a lack of chiropractic teaching programs in major universities. As a response to this challenge the Chiropractic Academy for Research Leadership, CARL, was created with the aim of develop a global network of successful early-career chiropractic researchers under the mentorship of three successful senior academics from Australia, Canada, and Denmark. The program centres upon an annual week-long program residential that rotates continental locations over the first three-year cycle and between residentials the CARL fellows work on self-initiated research and leadership initiatives. Through a competivite application process, the first cohort was selected and consists of 13 early career researchers from five professions in seven countries who represent diverse areas of interests of high relevance for chiropractic. The first residential was held in Odense, Denmark, with the second being planned in April 2018 in Edmonton, Canada, and the final residential to be held in Sydney, Australia in 2019.

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)0.018
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.003
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 head0.424
GPT teacher head0.476
Teacher spread0.052 · 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.

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

Citations15
Published2018
Admission routes3
Has abstractyes

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