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Taking the Pulse of Forensic Anthropology in Canada

2010· article· en· W2070205458 on OpenAlexaffvenueabout
Mark Skinner, Liam Clegg, Derek Congram, Anne Katzenberg, Richard A. Lazenby, Amy Z. Mundorff, Tanya R. Peckmann, Michael W. Spence, Susan Stratton, Kathryn Waterhouse

Bibliographic record

VenueCanadian Society of Forensic Science Journal · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of AlbertaKwantlen Polytechnic UniversityWestern UniversityUniversity of CalgarySaint Mary's UniversityUniversity of Northern British ColumbiaSimon Fraser University
Fundersnot available
KeywordsForensic anthropologyForensic scienceNeglectWork (physics)Public relationsTask forcePolitical scienceSociologyMedicinePublic administrationAnthropologyNursingEngineering

Abstract

fetched live from OpenAlex

The current state of forensic anthropology is evaluated by a limited cross-section of active practitioners from across Canada. The number of specialists undertaking casework in this area of forensic science is growing, as are expectations of the quality of our work from death investigative agencies nationally. However, the majority of forensic anthropologists in Canada are university-based and inadequately supported by their administrative units in terms of secure lab facilities and finances. Federal and Provincial funding agencies that could support research in this field and assist with creating infrastructure to meet emerging expectations of standards of forensic practice are by and large not doing so. Across Canada, unevenness of standards of training, practice and support reflects a lack of appreciation of forensic anthropology by society as a whole, as well as by funding agencies and the legal community. It also reflects the willingness of individual forensic anthropologists to accept this neglect and under-valuation of their work, likely because of a professional commitment to the task which they accept as a social responsibility. It is recommended that a national consensus of standards of practice, facilities and training be achieved among forensic anthropologists so as to place pressure on federal funding agencies in Canada to support forensic anthropology adequately in the future.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.634
Threshold uncertainty score1.000

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 studies0.0010.081
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.254
Teacher spread0.231 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations6
Published2010
Admission routes3
Has abstractyes

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