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A Workshop for Medical Students on Deafness and Hearing Impairments

2003· article· en· W2068319955 on OpenAlexaffabout
Elizabeth Lock

Bibliographic record

VenueAcademic Medicine · 2003
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedical educationCurriculumHearing impairedInclusion (mineral)Multidisciplinary approachPsychologyScope (computer science)AudiologyMulticulturalismMedicineFamily medicinePedagogy

Abstract

fetched live from OpenAlex

There is a current need to improve health care delivery to deaf and hearing-impaired persons. The author designed an educational workshop for medical students and others as an initial step to address this need. The workshop was offered electively during 1997 and 1998 to first-year and second-year medical students at Dalhousie University, Nova Scotia, Canada. The workshop involved a broad, multidisciplinary scope, may have been the first of its kind in Canada, and is still one of the few documented ways to approach medical education about deafness and hearing impairments. Attendees explored general information on hearing impairments, communication between the hearing-impaired patient and his or her physician, and multicultural, technological, and ethical aspects of caring for hearing-impaired patients. There was an initial questionnaire, group exercises, lectures, student interviews of volunteer deaf "patients," discussions, and a "hands-on" materials display. The workshop was a low-cost and easily reproducible method of educating medical students about hearing impairments. If found to be educationally effective through future research, this type of workshop may foster better care to deaf and hearing-impaired persons by inclusion into medical school and continuing education curricula.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.001
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 head0.086
GPT teacher head0.459
Teacher spread0.372 · 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.

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

Citations47
Published2003
Admission routes2
Has abstractyes

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