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Record W2341907709 · doi:10.1186/s40697-016-0117-6

Results of the 2014–2015 Canadian Society of Nephrology Workforce Survey

2016· article· en· W2341907709 on OpenAlexafffundabout
David Ward, Braden Manns, Sarah Gil, Flora Au, Joanne Kappel

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2016
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of SaskatchewanUniversity of Calgary
FundersCanadian Society of Nephrology
KeywordsWorkforceMedicineSubspecialtyNephrologyFamily medicineDemographicsInternal medicineDemography

Abstract

fetched live from OpenAlex

BACKGROUND: Nephrology was previously identified as a subspecialty with few Canadian employment opportunities, and in recent years, fewer trainees are choosing nephrology. OBJECTIVE: The objective of this study is to better understand the current Canadian adult nephrology workforce and the expected workforce trends over the next 5 years. DESIGN: This is an online self-administered survey. SETTING: This study is set in Canada. SURVEY PARTICIPANTS: Survey participants are Canadian adult nephrologists, including self-identified division heads. MEASUREMENTS: The measurements of this study are demographics, training, current practice characteristics, work hours, and projected workforce needs. METHODS: Survey questions were based on previous workforce surveys. Ethics approval was obtained through the University of Saskatchewan. The survey was piloted in both English and French and modified based on the feedback to ensure that responses accurately reflected the information desired. It was circulated to all identified Canadian nephrologists via an anonymous e-mail link for self-administration. Categorical data was aggregated, and free-text answers were thematically analyzed. Additional descriptive analysis was conducted by all authors. RESULTS: Five hundred ninety-two Canadian nephrologists were contacted and 48 % responded, with representation from all Canadian provinces. One third of the respondents were female, and the largest age cohort was 41-50 years. Most nephrologists are trained in Canada and 61 % completed additional training. The majority of the respondents (69.1 %) began working as a nephrologist immediately upon completion of fellowship training. Younger nephrologists reported more challenges in finding a job. Eighty percent of responding nephrologists were satisfied with their current work hours, 13.1 % will reduce work hours within 3 years, an additional 8.2 % will reduce work hours within 5 years, and a further 14.2 % will reduce work hours within 10 years. Nephrology division heads forecasted the number of clinical and academic nephrologists needed for the next 3 and 5 years. LIMITATIONS: The response rate was 48 %. Forecasted workforce needs are not indicative of guaranteed future positions. CONCLUSIONS: This Canadian Society of Nephrology workforce survey demonstrated the current workforce demographics, individual nephrologist future workforce plans, and projected nephrology division requirements for the next 3 and 5 years. Further work will need to be done to refine Canadian nephrology workforce planning with the development of a robust strategy that encompasses both societal and nephrologists' needs with the realities of employment.

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)0.006
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.009
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.278
Teacher spread0.256 · 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 designObservational
DomainIncentives
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

Citations9
Published2016
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Kidney Health and DiseaseSame topicDialysis and Renal Disease ManagementFrench-language works237,207