MétaCan
Menu
Back to cohort
Record W1989461489 · doi:10.12927/hcpol.2009.20814

Jennifer Zelmer: Healthcare Policy's New Editor-in-Chief

2009· article· fr· W1989461489 on OpenAlexvenueaboutno aff
Anton Hart

Bibliographic record

VenueHealthcare policy · 2009
Typearticle
Languagefr
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsHealth carePublic relationsTerminologyDeskOrder (exchange)Political scienceAction (physics)BusinessLaw

Abstract

fetched live from OpenAlex

The healthcare community is overwhelmed by torrents of information each and every day – some of it important, much of it not – and so a journal editor's role matters a great deal. The journal must, after all, make a difference. If the members of this community are to understand what is happening in healthcare and in society, and if they are presented with credible options and alternatives to respond, she will serve them well. If she can move them to action, she will be an inspiration. The right individual to take on the role of editor must be intelligent; well briefed about healthcare policy and practice; intimately familiar with data and information sources; linked directly to an international community of researchers, academics, payers, policy makers, managers and providers of care; and she will have a thorough understanding of the healthcare consumer. In addition to these credentials, she must be a leader, or no one will follow her. Finally, she must be highly organized in order to deal with the many proposals, manuscripts and reviews that cross her desk. A tall order. Allow me to introduce Dr. Jennifer Zelmer. Her current focus is the use of health systems performance data to make international comparisons. She is CEO of the International Health Terminology Standards Development Organisation (IHTSDO), based in Copenhagen. Previously, she was vice president for research and analysis at the Canadian Institute for Health Information (CIHI), where she initiated and oversaw an integrated program of analytical activities, including leading teams responsible for developing CIHI's annual report on healthcare in Canada. Prior to joining CIHI, she worked with a variety of health, academic and governmental organizations in Canada, Australia, Denmark and India, among other countries. She has also held such positions as adjunct lecturer at the University of Toronto and research associate with the Research Institute for Quantitative Studies in Economics and Population at McMaster University. Currently, she is a member of several health-related boards and advisory committees. She has a bachelor's degree in health information science and a doctorate in economics from McMaster University. Good currency. When Zelmer took her current position, Richard Alvarez, president and CEO of Canada Health Infoway, remarked that she “is a young, dynamic and talented professional who will bring vision, passion and energy to the development and establishment of IHTSDO. Canada's loss is truly the International Standards community's gain!” She was selected for this position based on her impressive track record of working in an international and political environment, and her extensive experience in successfully leading and motivating teams within a new organization. You will also want to hear from her mentor – Denis Protti, founder of the University of Victoria's School of Health Information Science. I have known Jennifer for over 15 years. Our first meeting was memorable. She came for an interview to enter our school. After conducting herself very well, she left the room as my colleagues and I completed our assessment forms. I opened the discussion with the comment that she was, in my opinion, an ideal and outstanding candidate. All agreed – there was really no need for any discussion. Faculty and students alike were constantly amazed how she could perform at such a high intellectual level – someone who is bright, personable and a doer. The Canadian healthcare system and the field of health informatics has been the lucky party. She could have gone into any other sector and been a star. Longwoods is honoured to support Jennifer Zelmer as she shares her talent and insight through the pages of Healthcare Policy. We welcome our new Editor-in-Chief.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.494
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.005
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0010.004

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 head0.050
GPT teacher head0.444
Teacher spread0.394 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
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

Citations1
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueHealthcare policySame topicPrimary Care and Health OutcomesFrench-language works237,207