MétaCan
Menu
Back to cohort
Record W2188692494

The Future of Clinician-Scientists in Canada

2004· article· en· W2188692494 on OpenAlexvenueaboutno aff
Matthew W. C. Chan

Bibliographic record

VenueJournal of The Canadian Dental Association · 2004
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsGraduation (instrument)IncentiveDebtMedical educationStudent debtEconomic shortagePosition (finance)Health careMedicineInstitutionPublic relationsPolitical sciencePsychologyGovernment (linguistics)FinanceBusinessEngineering
DOInot available

Abstract

fetched live from OpenAlex

Scientific research is an integral part of dentistry, bringing us new knowledge and different approaches to providing better patient care. Clinicians — our front-line health care providers — are in a unique position to raise novel scientific questions from clinical cases and to bring solutions from benchside to chairside. Yet the shortage of clinician-scientists has been a common theme in our Canadian dental schools in recent years. With the greying of faculty members, the challenge to sustain the existing level of clinician-scientists becomes even more difficult. How can we alleviate this growing concern? The answer seems to lie with the ability of universities to attract dental students into careers in academia — and to prepare them for such careers. Through my own experience and discussions with my fellow-students, there appear to be some common issues that deter students from becoming clinician-scientists. First, the financial burden of today’s dental students is a lot more than that of graduates from a decade ago. With rising tuition fees (which have almost doubled in the past 5 years), the average student will have a debt of about $100,000 or more by the time he or she graduates. The financial incentives of practising dentistry outweigh those of an academic career, especially in the early years following graduation when students are trying to repay their loans. Once students leave an academic institution, it becomes more difficult for them to return. 1,2 Further, the average age of graduating students is late 20s, when many are trying to start families. They believe the long hours required to establish a research program would not be compatible with family life. This perception is related to another problem: the lack of role models in our schools to mentor students into becoming clinicianscientists. The DDS/PhD who practises dentistry and is actively engaged in research is increasingly rare. Although the future looks bleak for our dental faculties, there are ways in which this crisis can be overcome. In the U.S., the National Institutes of Health (NIH) offers dental scientist fellowships that provide tuition support for dental students if they commit to a research career. 3 Should the Canadian Institutes of Health Research (CIHR) follow suit, this would help Canadian dental students become clinicianscientists by assisting them with their financial burden. This is not a novel idea in Canada. The Canadian Armed Forces have a Dental Officer Training Plan that helps subsidize dental education, in exchange for a period of service upon graduation. 4 The military usually has more applications than positions available. Sometimes, monetary rewards are not enough to persuade students to select a career in academic dentistry. A stimulating intellectual environment is also an important driving force in nurturing students to become clinician-scientists. One approach is to expose students to scientific research in the early stages of their education. I spent the summer break during my undergraduate years working in various research

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)0.015
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.985
Threshold uncertainty score0.929

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0460.011
Scholarly communication0.0270.007
Open science0.0060.015
Research integrity0.0160.024
Insufficient payload (model declined to judge)0.0530.008

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 head0.024
GPT teacher head0.339
Teacher spread0.315 · 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.

Study designNot applicable
DomainIncentives
GenreCommentary

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

Citations2
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueJournal of The Canadian Dental AssociationSame topicHealth and Medical Research ImpactsFrench-language works237,207