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Record W2124729060 · doi:10.1080/01421590310001653937

Design, delivery and evaluation of an email-based Continuing Professional Development course on outdoor air pollution and health

2004· article· en· W2124729060 on OpenAlexafffund
Erica Weir, David M. Stieb, Alan Abelsohn, Manson Mak, Tom Kosatsky

Bibliographic record

VenueMedical Teacher · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsMcGill UniversityHealth CanadaUniversity of TorontoMcMaster University
FundersCanadian Medical Association
KeywordsCourse (navigation)Medical educationProfessional developmentContinuing professional developmentPsychologyEnvironmental healthEnvironmental planningMedicineEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

The authors designed an email-based discussion forum with the objective of promoting and supporting peer discussion on the health effects of outdoor air pollution, linked to a recently published review article. Clinical cases served as stimulus material and participants were provided with an online toolbox of resources. Message postings from 27 participants were most frequent (92) during the first of four weeks and lowest (17) during the second, suggesting that some participants were overwhelmed by the initial volume. Evaluation of short-term impact completed by 16 participants indicated that the course was successful in improving some participants' knowledge. Evaluation three months after course completion by 20 participants revealed an impact on clinical practice. As an alternative to email, requiring participants to visit a web page to view and submit postings may avoid problems related to volume of messages. Controlled delivery of small portions of information tied to specific self-directed tasks is also recommended.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.034
GPT teacher head0.344
Teacher spread0.310 · 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

Citations8
Published2004
Admission routes2
Has abstractyes

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