Posts Tagged ‘cluster analysis’
What! Savages and primitive tribes? Who is Claude Levi-Strauss (1908-2009)
Posted by: adonis49 on: February 10, 2010
What! Savages and primitive tribes? (Feb. 10, 2010)
The late famous ethnologist and anthropologist Claude Levi-Strauss (1908-2009) said: “I gave up preserving primitive tribes; all that I am doing is recording their memory for later generations. Mankind is settling in mono-culture: Humanity is readying to producing mass civilization.”
Claude Levi-Strauss spent 5 years in the Amazon and Mato Grosso (1935-39) researching a few of their primitive tribes such as Caduveo, Bororo, Nambikwara, Munde, and Tupi-Kawahib.
Claude Levi-Strauss agrees with the prophetic remark of the physicist Neil Bohr who said in 1939:
“The traditional differences among cultures resemble the equivalent different manners of describing physical experiments”.
Claude gathered 3,000 photos and he needed 15 years of soul searching to gather enough courage and publish his first book “Sad Tropic, 1955” on his exploration missions.
Among the other masterpieces related to ethnology and anthropology we have “Structural Anthropology, 1958”; “The savage thinking, 1962”; “Mythology of the naked man, 1964”; “Seeing, listening, and reading, 1993”; and “Saudades of Sao Paulo, 1994”.
Primitive tribes are going extinct fast.
The trend is man-made expansion and exploitation that started by European colonial adventure in the 16th century, and particularly in the 19th century. A couple of decades ago, tribes in the Amazon Forest went extinct because Texaco polluted and ruined the ecological make-up for its oil-well extraction processes. Read note 2.
In “Sad tropic”, Levi-Strauss was pretty candid and wrote:
“I hate to travel and to explore. Should I recount the insipid details of a servitude to weeks and months of traveling, of hunger, fatigue, and illnesses? Should I tell of the toils for daily maintenance and upkeep as in routine military service? The amounts of efforts expanded on ethnological research do not confer a price to the negative aspects of the job. Truth can be divulged after all the gangue are stripped off.”
In 1940, the Vichy government whisked Levi-Strauss with three other French scholars to the USA because “with such a name you are doomed in France.” Levi-Strauss said that “I have never felt Jewish even though my parents were Jews. I did experience the difficulties and problems of being Jew in schools and universities. I do not comprehend the inventions of the Catholic Church councils relative to Trinity, trans-substantiation, or communion of the Saints. I have no inclinations of trying to comprehend these abstract notions. Christianity exercises aesthetic seduction on me.”
Levi-Strauss stresses that “the longer we get attached to ethnology, the more we keep our distances of current societies: the essential and dramatic characteristics of the present will not count heavily in the perspectives of several centuries later. Individuality is more prevalent in primitive tribes than in modern civilization. Ethnology respects history, though it does not extend to it any privileged value. History is a complementary research that deploys human societies over time, while ethnology extends the research over space.”
Anthropology extends the impression of going to the extreme limits of what was the goal of philosophy in witnessing the totality of human experiences. A scholar does not offer real answers: his role is to formulate pertinent clear questions.
Symbols have no intrinsic or invariable significance: they have meaning only within the context. This significance is foremost of position.
Myth is started by an individual and then is taken over by the original group and fine tuned progressively. Levi-Strauss claims that the main characteristic in myths is the beauty emanating from the imaginative stories. There is this intelligent emotion that story of myth, painting, sculpture, or music strikes us head on and makes us feel that we comprehend the global configuration.
Levi-Strauss is known for establishing “structuralism” in the domain of human sciences. If you read what is structuralism from non-scientific critics, you will not be more intelligent than before.
Structuralism in human sciences is a procedure of untangling the invariant characteristics of societies (for example, primitive societies) within the fundamental constraints of geography and environment on their specific structures. Studying primitive tribes is an excellent venue to extrapolate results to other societies enjoying the same restrictive localities.
(There are many statistical packages specifically designed to sort out the main characteristics or dimensions that group the cluster of categorical data. You have discriminant analysis, cluster analysis, and factors analysis experimental designs that do not differentiate among variables, simply because the purpose is fundamentally to investigate the main factors that come into play, for later well designed experiment of cause and effects. See note 3)
Note 1: Claude Levi-Strauss was born in Belgium and studied philosophy. He was offered a teaching position of sociology in Sao Paulo (Brazil) in 1935. During the period (1935-39), Claude Levi-Strauss directed several missions in the Amazon and Mato Grosso to investigate primitive tribes. He taught at New School Social research in New York and then was appointed cultural attaché to the French Embassy in Washington DC in 1945. Levi-Strauss was nominated director of comparative religion of people with no written languages in Paris (1949). He was appointed professor of social anthropology at the “College de France” till 1982. He was elected to the French Academy in 1973.
Note 2: At the current rate of modernization and deforestation most of the aborigine tribes would disappear within a few decades. Many civilizations have vanished but a few have managed to survive precariously so far.
Currently we still have the ethnic Saamis (Norway and Finland), Inuits (Siberia, Alaska, and Canada), Ainous (Japan), Indians (USA and Canada), Zapotec (Mexico), Mosquitos (Nicaragua), Quiches (Guatemala), Cunas (Panama), Yanomamis and Guaranis (Brazil), Galibis and Akawaios (Guyana), Paez ans Guambianos (Colombia), Waoranis (Equator), Amueshas (Peru), Chimanes (Bolivia), Araucans (Chili), Touaregs and Bororos (Sahel in Northern Africa), Tigres (Ethiopia and Somalia), Dinkas (Sudan), Masais (Kenya and Tanzania), Pygmees (Zaire), Sans or Bushmen (Namibia and Botswana), Kalingas (Philippines), Kachins and Rohingas (Myanmar or Birmani), Hmongs (Laos), Santals and Gonds (India), Punans (Malaysia), Uzbeks and Tadjiks (Afghanistan), Aborigines (Australia), Maoris (New Zealand), Papous (New Guinea).
Note 3: Dimensions or factors are sorted out and data are forced to cluster along these dimensions and then the dimensions are given names (a kind of art). Once names are extended to dimensions then it becomes hard to change their connotations.
For example, quantitative psychology, marketing, and sociology use these structural analyses to find out complexity, customs, traditions, cooking specifications, and customer preferences, qualitative notions of beauty, parenting, or associations among the cluster of data.
How objective and scientific are experiments?
Posted by: adonis49 on: July 6, 2009
Article #30 of “What is Human Factors in Engineering?”; December 27, 2005
“How objective and scientific are experiments?”
If we narrow this article to the statistical analysis of experiments and without going into details suffice us to mention a few controversies. First, let us do a chronology of the various paradigms in statistics and statistical algorithms. From a European perspective Pascal is believed to have started probability theory in1654.
LaPlace and Legendre contributed to the Least-Squares algorithm for how to fit a model to data (1750-1810)
Gauss developed the geometry and algebra of the multivariate normal distribution (1800’s)
Galton studied regression between two variables (1885) and Pearson the correlation coefficient in 1895.
Fisher, Snedecor and Sheffe concurrently worked on experimental design and analysis of variance algorithm (ANOVA) to statistically test the population distribution under the assumptions of normality in the 1920’s.
The data analyses of non distribution base samples to fit models to data showing structural features were developed by Thurstone in Factor Analysis, by Young and Householder (1935) in Multidimensional scaling and Cluster analysis algorithms.
Joreskog, K. G developed in 1973 the algorithm of a general method for estimating a linear structural relational equation labeled LISREL that analyses the relationships among latent variables linked to operationalized indicators. This general method considers as special cases path analysis recursive or non recursive as well as Factors analysis.
John Tukey and Mosteller concentrated on studying exploratory data analysis to fit mathematical and geometric models to data showing both structural and residual, and thus complementing confirmatory or inferential analyses.
There are divergent paradigms in the following concepts: first, the suitability of data measurements according to measurement theory versus the distribution properties of the variable of interest (S. S. Stevens versus I. R. Savage in the 60’s); second, the need to investigate real world data prior to applying any statistical package (data snooping) so that if you perform serious detective work on the data and torture it long enough it will confess and open many ways to understand its underlying behavior (John Tukey); thus increased emphasis on graphs of individual data points and plotting to investigate the preliminary screening so as to ensure that the summary statistics selected are truly relevant to the data at hand.
Third, the application of the Bayesian approach from the consumer or decision maker viewpoint which provide the final probability against evidence instead of the investigator standard acceptance of a p-value to rejecting a hypothesis (read the “Illusion of Objectivity” by James Berger and Donald Berry, 1988).
Fourth, the selection of an investigator for a statistical package that he is familiar with instead of the appropriate statistics for the research in question; The acceptance of untenable assumptions on population distributions and computing unrealistic parameters simply because the investigator is not trained to understanding or interpreting alternative statistical methods of nonparametric or distribution freer population methods.
Fifth, there are examples of investigators adopting explanatory statistical packages to torture data into divulging confusing causative variables while, in fact, the science is already well established in the domain to specifically determine exhaustively the causative factors simply because the investigator is not versed in mathematics or physics (“Tom Swift and his electric factor analysis machine by J. Scott Armstrong, 1967).
Sixth, there is a need to the “mathematization of behavioral sciences” (Skelum, 1969) which involves the development of mathematically stated theories leading to quantitative predictions of behavior and to derivation from the axioms of the theory of a multitude of empirically testable predictions. Thus, instead of testing verbal model as to the null hypothesis, an adequate mathematical model account for both variability and regularity in behavior and the appropriate statistical model is implied by the axioms of the model itself. Another advantage is that attention is turned to measuring goodness of fit, range of phenomena handled by the model and ability to generating counterintuitive predictions.
This discussion is an attempt to emphasize the concept of experimentation as a structured theory and that the current easy and cheap computational potentials should be subservient to the theory so that data are transformed to answer definite and clear questions. The Human Factors practitioner, whom should be multidisciplinary in order to master the human and physical sciences, is hard hit by the need of performing complex scientific experiments involving human subjects and yet required to yield practical recommendations for the applied engineering fields.
No wonder Human Factors professionals are confused in their purposes and ill appreciated by the other discipline unless a hybrid kind of scientists are generated from a structural combination of engineering discipline and modern experimental methods and statistical algorithms.
However, Human Factors engineers who have an undergraduate engineering discipline and a higher degree in experimental research and statistical analyses training can be better positioned to handle research involving mathematical modeling of theories in sciences.
The fixed mindedness in adolescents reminds us of the mind fix of old people with the assumption that the mind has the potential flexibility to grow while young.
You may look young masking and old mind or look older and exhibiting a younger mind; it is your choice how much time and energy you are willing to invest for acquiring knowledge.
