MétaCan
Menu
Back to cohort
Record W2594094256 · doi:10.1108/ijem-04-2016-0068

Questioning clerkship: applying Popper’s evolutionary analysis of learning to medical student training

2017· article· en· W2594094256 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

VenueInternational Journal of Educational Management · 2017
Typearticle
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsUniversity of OttawaWestern University
Fundersnot available
KeywordsOriginalityPositivismValue (mathematics)Process (computing)PsychologySociologyPedagogyMathematics educationEpistemologyMedical educationComputer scienceMedicineCreativitySocial psychology

Abstract

fetched live from OpenAlex

Purpose Through a series of critical discussions on Karl Popper’s evolutionary analysis of learning and the non-authoritarian values it promotes, the purpose of this paper is to advocate a Popperian approach for building medical student knowledge. Specifically, it challenges positivist assumptions that permeate the design and management of many educational institutions, including teaching hospitals, by considering what does and does not happen when learning takes place. Design/methodology/approach To illustrate how Popper’s approach differs from such a conception of learning, the paper examines the exchange between a preceptor (Sam) and a medical student (Lisa). The following exchange is based on the observations during a team meeting in a Canadian teaching hospital. The authors sent the transcript of the observation to Lisa for her comments. The statements in italics represent Lisa’s additions. Pseudonyms are used to protect the identity of participants in the exchange. Findings Popper’s evolutionary analysis of learning and the Objective Knowledge Growth Framework provide a means of managing specific aspects of one’s education through engaging in this learning process. Although this approach to teaching and decision making takes time to master, it does not require reconstituting existing institutional arrangements before it can be implemented in hospitals. Instead, it asks medical students, teachers and practitioners to be open to the theoretical underpinnings of the approach and to view knowledge growth as a process of systematic trial and error elimination. Originality/value This paper is original in its conceptualisation and may well become a classic in education circles. It draws on Popper’s philosophical arguments and enters into a much needed discourse for teaching and learning.

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)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.041
GPT teacher head0.448
Teacher spread0.406 · 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