History of anthropology och data

Early forensic analysis in Europe

• Johann Christoph Andreas Mayer - realised fingerprints were unique to individuals in 1788

• Franz Joseph Gall - Developed Phrenology (looking at lumps and bumps on your skull and equating that to brain shape)

Forensics during the 19th century in Europa

• Early toxicology studies

• More regimented fingerprint analysis

• Blood type detection

• Alphonse Bertillon - Founder of anthropometry (measuring proportions of the human body) and standardized mughots

• Juan Vucetich - Created the frist mthod of recording an individual’s fingerprints

• First fingerprint bureau in 1892

Forensics in the US: when was the Formative Period?

1800-1938

What happened during the Formative Period

• Forensic anthropology was conducted by physicians, anatomists, and some physical anthropologists

• Practitioners were either informally trained in the identification of skeletal remains or self-taught

• Thomas Dwight - Founder of forensic anthropology in the US and developed methods for estimating sex, age and stature from skeletons

  • The identification of the human skeleton: a medicalegal study

• Thomas Wingate Todd - Created the first large collection of human skeletons in 1912 and developed a comprehensive sex estimation method in the pelvis

Forensics in the US: when was the Consolidation Period

1939 to 1971

What happened during the Consolidation Period

• Forensic anthropology was employed to identify war dead from WWII and the korean war

• Wilton Marion Krogman

  • Interested in dental anthropology

  • Child growth and development

  • Development of Forensic Anthropology as a discipline

Forensics in the US: When was the Establishment Period

1972-2006

What happened during the Establishment Period?

• Forensic Anthropology became more professionalized

• Creation of the Physical Anthropology section of the American Academy of Forensic Sciences in 1972

• William M.Bass - Initiated the “Body Farm” in Knoxville, Tennessee in 1981

• Clyde C Snow - Developed the forensic anthropology protocol we use today

  • Worked with Argentinian human rights groups documenting and exhuming mass graves

  • Created the Guatemalan Forensic Anthropology team in 1991

Forensics in the US: When was the Expansion Period

2007-today

What happened during the Expansion Period

• Expansion of the science used in Forensic Anthropology

• Formation for the Scientific Working Group for Forensic Anthropology (SWGANTH) in 2008

  • They develop consensus best-practice guidlines and establish minimum standards for the Forensic Anthropology discipline

• Amy Mundorff - Worked to identify remains from 9/11

  • Forensic identification expanded out of the medicolegal sphere to include mass disasters

Vad är continuous data?

Data that represents positions along continuum and can be broken down into smaller units of measure e.g metric measurements of mm, cm, meters, km etc

Vad är discontinuous/discrete data

Data that have distinct values e.g categorical data of presence/absence, open/closed

What is Nominal Data

• Measures discrete data

• Mutually exclusive and exhaustive categories

• Responses cannot be ranked

• eg. Coulour and sex estimation

What is original data?

• Measures discrete data

• Mutually exclusive and exhaustive categories

• Ranked or ordered categories

• Data har assymetrical properties (if A>B and B>C then A>C)

• Amount of chang between categories cannot be assessed

• eg. Size (small, medium large), cranial suture closure (open, partial closure, signifciatn closure, oblierated)

Vad är Interval Data?

• Equal distance between data points

• Can be either discrete or continuous data

• Measurement between ranks has a standardized unit of measure

• Lacksa true “0” point, meaning 0 is not equal nil

• Amount of change between two variables can be accurately assessed

• E.g temperatures, time since death

Vad är Ration Data?

• Has an absolute 0 (absence of a variable)

• Equal distance bewteen all intervals

• Continuous data

• Values can be compared with one another

• eg. income (0 dollars means no dollars), length (cm)

What is mode

• The most frequently occuring score in teh data

• Will want to use mode for discontinuous data

• Nominal, Ordinal, Interval and Ratio data

• Not influenced by outliers that can skew the data

What is Median

• The score in the middle of the dataset

• Ordinal, Interval and Ratio data

• True model of central tendency

• Outliers impact the median only slightly

What is mean

• Average unit of data

• Interval and ratio data

• Sensitive to the influence of outliers, especially in small sample sizes

• In a normal distribution the mean, mode and median are similar

Sources of error

• Random Error: unknown error eg mistakes

• Systematic Error: Errors that are consistently biased, eg flaw in the measuring tool, flaws between observers

• Negligent Errors. incorrect operations (observer error)

Reducing error

• Data cleaning - Regularly check data for mistakes

• Regular maintenance and calibration of equipment

• Standardized training or instruction on the operation of equipment or execution of a method

• Conducting studies to identify negligent error in measurement (intra/inter observer error)

• Identifying “acceptable” levels of error

How do you test for intraobserver (one person) error

• Repeat a measurement three times on three different days

  • Are the measurements accurate (the correct answer)?

  • Are the measurements precise (the same answer)?

How do you test for interobserver error?

Compare measurment results from multiple observers on the same specimen

• Calculate the difference between measurements from a known measurement and present as a percentage

Daubert criteria for reliable scientif knowledge

• Theory or technique must be testable or tested

• Have been subjected to peer review and publication

• Have known or potential error rates

• Existence and maintenance of standards controlling operation

• Must be widely accepted by experts in the field

• To be considered an expert “(t)he subject matter of the inquiry must be such that ordinary people are unlikely to form a correct judgement about it, if unassisted by persons with special knowledge” Kelliher (Village of) v. Smith (1931) S.C.R: 672, p 684

• Expert evidence must be both necessary and relevant in assisting the jury/judge. Experts must be properly qualified to testify on the topic

3 types of expert opinion

• Specualtion - a statmenet based on little or no data

• Possible - offering an opinion on a characterstic or event occuring from unknown parameters

• Probable - Opinions absed on known parameters