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Record W1864986828

Case Study of Generic Competencies Assessment

2011· article· en· W1864986828 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePharmacy Education · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Tools and Methods
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBachelorCommitPharmacyCompetency assessmentProcess (computing)Medical educationComputer scienceEngineering managementPsychologyKnowledge managementMedicineEngineeringNursingPolitical scienceDatabase
DOInot available

Abstract

fetched live from OpenAlex

Introduction: In 2007, the Faculty of Pharmacy of Universite de Montreal replaced its bachelor’s program with an all-new Doctor of Pharmacy Program, which uses a competency-based approach. In that setting, development of tools to monitor students’ progress in regards to generic competency was of crucial importance. Description of assessment method: Generic competencies and competency elements to be assessed were defined and assigned to each program course, and assessment tools were designed to create a generic competency profile for each student. Evaluation: Results from the first two cohorts of 200 students show that the new process meets the Faculty’s objectives. Strong agreement can already be seen on both exceptional and problem students, suggesting that our method is relatively reliable. Future plans: The information technology platform will be improved to allow students to view their individual file, on demand. We believe that this project will contribute to promoting generic competencies development in our students and help them sincerely commit to this goal.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.391
GPT teacher head0.540
Teacher spread0.149 · 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