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Record W2008233978 · doi:10.1097/acm.0b013e3181d85a4e

The Processes and Dimensions of Informed Self-Assessment: A Conceptual Model

2010· article· en· W2008233978 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

VenueAcademic Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSelf-assessmentGrounded theoryPsychologyFocus groupPsychological interventionMedical educationNonprobability samplingProcess (computing)Qualitative researchApplied psychologySocial psychologyMedicineComputer scienceSociology

Abstract

fetched live from OpenAlex

PURPOSE: To determine how learners and physicians engaged in various structured interventions to inform self-assessment, how they perceived and used self-assessment in clinical learning and practice, and the components and processes comprising informed self-assessment and factors that influence these. METHOD: This was a qualitative study guided by principles of grounded theory. Using purposive sampling, eight programs were selected in Canada, the United States, the United Kingdom, the Netherlands, and Belgium, representing low, medium, and high degrees of structure/rigor in self-assessment activities. In 2008, 17 focus groups were conducted with 134 participants (53 undergraduate learners, 32 postgraduate learners, 49 physicians). Focus-group transcripts were analyzed interactively and iteratively by the research team to identify themes and compare and confirm findings. RESULTS: Informed self-assessment appeared as a flexible, dynamic process of accessing, interpreting, and responding to varied external and internal data. It was characterized by multiple tensions arising from complex interactions among competing internal and external data and multiple influencing conditions. The complex process was evident across the continuum of medical education and practice. A conceptual model of informed self-assessment emerged. CONCLUSIONS: Central challenges to informing self-assessment are the dynamic interrelationships and underlying tensions among the components comprising self-assessment. Realizing this increases understanding of why self-assessment accuracy seems frequently unreliable. Findings suggest the need for attention to the varied influencing conditions and inherent tensions to progress in understanding self-assessment, how it is informed, and its role in self-directed learning and professional self-regulation. Informed self-assessment is a multidimensional, complex construct requiring further research.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.374
Teacher spread0.351 · 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