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Cabin Fever: an innovation in faculty development for rural preceptors

2005· article· en· W2088799658 on OpenAlexaffabout
Heather Armson, Rod Crutcher, Doug Myhre

Bibliographic record

VenueMedical Education · 2005
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsSuncor Energy (Canada)
Fundersnot available
KeywordsContext (archaeology)SpecialtyAttendanceRecreationRural areaMedical educationPracticumMedicineFamily medicinePsychologyPolitical scienceGeography

Abstract

fetched live from OpenAlex

Context and setting A new rural family medicine residency programme was established in Alberta, Canada in 2000. This group of 20 rural-based residents, in addition to the urban-based residents, are being trained in 21 rural and regional sites in Alberta over a 2-year period. One early challenge was that of faculty development (FD) for the 140 family medicine and specialty preceptors, most of whom were new to their roles as clinical teachers. Why the idea was necessary Traditional urban-based FD was neither congruent with the location and philosophy of the rural-based programme, nor appropriate, given the programme FD goals. The Cabin Fever retreat was established with the overarching goal of supporting the recruitment and retention efforts of the Alberta Rural Physician Action Plan as support from the main academic centres has been shown to stabilise manpower in underserviced areas. Each FD retreat has had 2 focused objectives: context-specific preparation of preceptors for their new roles in both teaching and evaluation of clinical skills, and networking among rural preceptors and their families. What was done The retreat was organised in a winter recreational setting. In a co-operative manner, the timing of other FD opportunities in the province were considered. This format was chosen as interruptions from the demands of practice were minimised, and opportunities for networking and social activities were readily available. The attendance of family members was explicitly encouraged – and funded – because of their crucial contribution to successful rural practice. The FD retreat is held each year on the same weekend in February. It takes place over 3 days, with mornings focused on educational activities and afternoons left unstructured. Participants and their families reconvene for an evening meal in which exemplars are honoured and the contribution of families to programme success acknowledged. The formal educational programme consists of 1 plenary speaker on the first day, followed by small group workshops. The workshop topics are based on a needs assessment coupled with feedback and suggestions from participants and residents from the previous year. The workshops are divided into 3 streams, with 1 for novice teachers, another for experienced teachers and a third for those interested in the theoretical foundations of education. Preceptors self-select into each stream and are allowed to cross over streams if they wish. Rural preceptors are actively sought to facilitate or co-facilitate workshops. Workshop facilitators are encouraged to use an interactive format with practice-enhancing strategies where appropriate (i.e. role play, videotape review and Internet access). Evaluation of results and impact Participants rate the retreat format, content and practice applicability very highly. There are numerous comments each year on the positive impact of actively including family members. Preceptors are asked to commit to specific teaching changes for each workshop they attend and the majority of participants do so. Next steps will include ensuring that each rural teaching site is represented at the retreat and that participants are supported in sharing the knowledge and skills gained with their site co-preceptors. A final step will involve the transfer of the retreat planning and delivery entirely to the rural preceptors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.038
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.090
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0090.010
Scholarly communication0.0090.004
Open science0.0070.011
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.064
GPT teacher head0.502
Teacher spread0.438 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

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Citations1
Published2005
Admission routes2
Has abstractyes

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