Introduction to Ancient Stone Debitage

Debitage,  pronounced in English roughly DEB-ih-tahzhs, is an artifact type, the collective term used by archaeologists to refer to the sharp-edged waste material left over when a flintknapper creates a stone tool (that is, knaps flint). The process of making a stone tool is rather like sculpture, in that it involves whittling down a block of stone by removing unwanted pieces until the sculptor/flint knapper achieves the final product. Debitage refers to those unneeded stone fragments. Debitage is the French term for this material, but it is commonly used in the scholarly literature in most other languages, including English. Other terms in English include waste flakes, stone chips, and chipping debris; all of these refer to the stone fragments left over as a waste product created when a worker produces a stone tool. Those terms also refer to chipping debris leftover when a stone tool is repaired or refined. Why is Debitage Interesting? Scholars are interested in the stone flakes left behind by flintknappers for a number of reasons. The pile of debris is the location where stone tool production took place, even if the tool itself was taken away: that alone tells archaeologists about where people lived and worked in the past. The flakes also hold information about the type of stone used to make a stone tool, as well as the technology, the steps taken in the manufacturing process. Some of the waste flakes may be used as tools themselves, to scrape plants or cut meat for example, but by and large, the word debitage refers to those pieces which have not been reused. Whether the flakes were used as a tool or not, debitage accounts for the oldest evidence discovered for human-like behaviors: we know ancient people were making stone tools because we have found purposeful flaking debris even if we dont know what was being made. And as such, they have been recognized as an artifact type since the first decades of the 20th century. Analyzing Debitage Debitage analysis is the systematic study of those chipped stone flakes. The most common study of debitage involves simple (or complex) cataloging of the flakes characteristics, such as source material, length, width, weight, thickness, flaking scars, and the evidence of heat-treatment among many others. Given that there can be thousands or tens of thousands of pieces of debitage from a site, data from all of those flakes definitely qualifies as big data. In addition, analytical studies have attempted to classify the flakes by step in the tool-making process. In general, a stone tool is made by removing the largest pieces first, then the pieces get smaller and smaller as the tool gets refined and shaped. A popular tool-based debitage typology in the late 20th century consisted of categorizing flakes into three stages: primary, secondary, and tertiary flakes. These rough categories were thought to reflect a very specific set of flake removal processes: primary flakes were removed from a block of stone first, then secondary, and finally tertiary flakes. Defining those three categories was based on size and the percentage of the cortex (unmodified stone) left on the waste flake. Refitting, putting the stone pieces back together whether simply one flake to another or reconstructing an entire stone tool, was originally quite pain-staking and labor-intensive. More recent tool-based imaging processes have refined and built on this technique considerably. Other Analytical Types One of the problems with debitage analysis is there is just so much debitage. The construction of one tool from a block of stone can produce hundreds if not thousands of waste flakes of all shapes and sizes. As a result, studies of debitage as part of the study of all stone artifacts at a given site are frequently completed using mass analysis techniques. Size grading by using a set of graduated screens to sort debitage is often used. Researchers also sort the flakes into categories on a variety of attributes and then count and weigh the total in each category to estimate types of flaking activities. Piece-plotting of the distribution of debitage has been used, when it can be determined that the scatter of flakes has laid relatively undisturbed since its deposition. That study informs the researcher about the mechanics of flint-working activities. As a parallel study, an experimental reproduction of flint knapping has been used to build a suitable comparison of debitage scatters and production techniques. Microwear analysis is the study of the edge damage and pitting of debitage using a low- or high-power microscope, and it is generally reserved for debitage that has likely been used as a tool. Sources and Recent Studies A great source for information about all types of Lithic Analysis is Roger Graces Stone Age Reference Collection. The late Tony Bakers excellent lithics site  while now outdated still contains buckets of useful information based on his understanding of the mechanical processes he learned in his own flintknapping experiments. Ahler, Stanley A. Mass Analysis of Flaking Debris: Studying the Forest Instead of the Tree. In Alternative Approaches to Lithic Analysis. The Archaeological Papers of the American Anthropological Association. Eds. Henry, D. O., and George H. Odell. Vol. 1 (1989): 85-118. Print. Andrefsky Jr., William. The Analysis of Stone Tool Procurement, Production, and Maintenance. Journal of Archaeological Research 17.1 (2009): 65-103. Print. —. The Application and Misapplication of Mass Analysis in Lithic Debitage Studies. Journal of Archaeological Science 34.3 (2007): 392-402. Print. Bradbury, Andrew P., and Philip J. Carr. Non-Metric Continuum-Based Flake Analysis. Lithic Technology 39.1 (2014): 20-38. Print. Chazan, Michael. Technological Perspectives on the Upper Paleolithic. Evolutionary Anthropology: Issues, News, and Reviews 19.2 (2010): 57-65. Print. Eerkens, Jelmer W., et al. Reduction Strategies and Geochemical Characterization of Lithic Assemblages: A Comparison of Three Case Studies from Western North America. American Antiquity 72.3 (2007): 585-97. Print. Eren, Metin I., and Stephen J. Lycett. Why Levallois? A Morphometric Comparison of Experimental ‘Preferential’ Levallois Flakes Versus Debitage Flakes. PLoS ONE 7.1 (2012): e29273. Print. Frahm, Ellery, et al. Sourcing Geochemically Identical Obsidian: Multiscalar Magnetic Variations in the Gutansar Volcanic Complex and Implications for Palaeolithic Research in Armenia. Journal of Archaeological Science 47.0 (2014): 164-78. Print. Hayden, Brian, Edward Bakewell, and Rob Gargett. The Worlds Longest-Lived Corporate Group: Lithic Analysis Reveals Prehistoric Social Organization near Lillooet, British Columbia. American Antiquity 61.2 (1996): 341-56. Print. Hiscock, Peter. Quantifying the Size of Artefact Assemblages. Journal of Archaeological Science 29.3 (2002): 251-58. Print. Pirie, Anne. Constructing Prehistory: Lithic Analysis in the Levantine Epipaleolithic. The Journal of the Royal Anthropological Institute 10.3 (2004): 675-703. Print. Shea, John J. The Middle Stone Age Archaeology of the Lower Omo Valley Kibish Formation: Excavations, Lithic Assemblages, and Inferred Patterns of Early Homo Sapiens Behavior. Journal of Human Evolution 55.3 (2008): 448-85. Print. Shott, Michael J. The Quantification Problem in Stone Tool Assemblages. American Antiquity 65.4 (2000): 725-38. Print. Sullivan, Alan P. III, and Kenneth C. Rozen. Debitage Analysis and Archaeological Interpretation. American Antiquity 50.4 (1985): 755-79. Print. Wallace, Ian J., and John J. Shea. Mobility Patterns and Core Technologies in the Middle Paleolithic of the Levant. Journal of Archaeological Science 33 (2006): 1293-309. Print. Williams, Justin P., and William Andrefsky Jr. Debitage Variability among Multiple Flint Knappers. Journal of Archaeological Science 38.4 (2011): 865-72. Print.

European Justification of Colonization of Asia and Africa...

The principle justification offered by the Europeans for their colonization of Asia Africa was the moral and technological superiority of the western world. As the Europeans saw it, the spread of the European way of life would substantially increase living standards for the colonized. While economic reasons were obviously the primary impetus for colonial expansion, the Europeans believed that they were not only improving the natives’ conditions, but they were saving their mortal souls by bringing Christianity to them. Over time, the technologically advanced way of life came to be associated with Europe, and with Europeans. This is the cause of the racist and social Darwinist undertones in the documents. First, Europeans use†¦show more content†¦The second justification is the welfare of the colonized nation. According to the majority of the documents given, assimilation into the world economy boosted the economy of the colonized nation, thus increasing the gener al well-being in said nation. Additionally, the colonizing nation would spread new technology, including things like medicine and agricultural technology. Of course, the colonizer would not just hand out life saving technology and then leave. Usually, the colonized nation would use the new technology under the supervision of the colonizer. The example of India proves this point. India benefited greatly from industrialization, which was brought about by the British. However, when the British discovered that India’s industrialization would cut them off from valuable raw materials, they halted the industrialization process, leaving India in very bad shape. If the British had allowed India to industrialize, the world would probably be a very different place today. Document 3 shows a cartoon that illustrates the point above. 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CAPM’s Contribution to the Stock Market Free Essays

The Capital Asset Pricing Model (CAPM) is a mathematical, analytical formula to help investors make the wisest decisions on the stock market. Before purchasing a common stock, an investor may use the CAPM (a mathematical formula) to estimate its expected returns. The Model may be used for all kinds of assets. We will write a custom essay sample on CAPM’s Contribution to the Stock Market or any similar topic only for you Order Now In brief, the CAPM helps to explain â€Å"the relationship between the risk of a particular asset or stock, its market price, and the expected return to the investor (â€Å"Capital Asset Pricing Model or CAPM,† 2007). By using CAPM as a tool to project expected returns from stocks, investors automatically affect the demand and prices of stocks sold on the market. The CAPM starts out with the assumption that there are two kinds of risks that must be assessed before an investment decision is made. Systematic risk includes risks facing the market as a whole and that cannot be dampened through portfolio diversification. Examples of systematic risks include rates of interest and economic slumps (McClure, 2008). While systematic risks must affect all stocks at the same time, unsystematic risks or specific risks are risks that are â€Å"specific to individual stocks and can be diversified away as the investor increases the number of stocks in his or her portfolio (McClure). † Of course, good investors are well-versed in investment theories such as the modern portfolio theory, which clearly states that diversification cannot resolve the issue of systematic risks, although specific risks may be easily handled by diversifying an investment portfolio. CAPM was developed as a way to address the issues raised by the modern portfolio theory. This Model is a tool to measure systematic risks as well (McClure). The Risk Glossary explains the importance of estimating systematic risk before the formula for measuring such risk is described: According to CAPM, the marketplace compensates investors for taking systematic risk but not for taking specific risk. This is because specific risk can be diversified away. When an nvestor holds the market portfolio, each individual asset in that portfolio entails specific risk, but through diversification, the investor’s net exposure is just the systematic risk of the market portfolio. Systematic risk can be measured using beta. According to CAPM, the expected return of a stock equals the risk-free rate plus the portfolio’s beta multiplied by the expected excess return of the market portfolio. Specifically, let and be random variables for the simple returns of the stock and the market ove r some specified period. Let be the known risk-free rate, also expressed as a simple return, and let be the stock’s beta. Then where E denotes an expectation (â€Å"Capital Asset Pricing Model,† 1996). The formula of CAPM is considered its conclusion (â€Å"Capital Asset Pricing Model†). To put it simply, the formula states that â€Å"excess expected return† of a stock is dependent on the beta of the stock rather than the stock’s volatility (â€Å"Capital Asset Pricing Model†). The same can be stated for an investment portfolio. Another way to explain the formula is that â€Å"the stock’s excess expected return over the risk-free rate equals its beta times the market’s expected excess return over the risk free rate (â€Å"Capital Asset Pricing Model†). † Or, excess expected return from a stock is dependent on systematic risk rather than the total of risks (â€Å"Capital Asset Pricing Model†). As suggested previously, by knowing the beta and expected returns for a certain stock or asset, investors are able to bid up or down its price. Expected returns are adjusted so long as the formula has not been satisfied. Thus, the Capital Asset Pricing Model ends up predicting the equilibrium price of a stock or asset. One of the assumptions of the model is that all investors agree on the expected return of certain stock or asset as well as the beta. Although this assumption is unrealistic, the CAPM is believed to affect the stock market by urging investors to raise the demand for particular assets or stocks as compared to others, based on the information they obtain through the use of the Model (â€Å"Capital Asset Pricing Model†). Apart from the unrealistic assumption of CAPM mentioned above, there are other problems with the Model that experts have identified by way of research. As an example, Eugene Fama and Kenneth French, upon considering expected returns on the American Stock Exchange, Nasdaq and the New York Stock Exchange for a period of 27 years, found that the differences of beta do not consistently describe the performance of stocks (McClure). McClure reports that the study conducted by Fama and French is not the only one that raised doubts about the validity of the Capital Asset Pricing Model. A major problem with the Model is the fact that beta cannot be used as a sure predictor of the reaction of stocks to various changes. All the same, the CAPM continues to be used by countless investors around the globe (McClure). In other words, beta continues to affect investment decisions that run the stock market day after day. References Capital Asset Pricing Model. (1996). Risk Glossary. Retrieved Nov 4, 2008, from http://www.riskglossary.com/link/capital_asset_pricing_model.htm. Capital Asset Pricing Model or CAPM. (2007). Money Zine. Retrieved Nov 4, 2008, from http://www.money-zine.com/Investing/Stocks/Capital-Asset-Pricing-Model-or-CAPM/. McClure, B. (2008). The Capital Asset Pricing Model: An Overview. Investopedia. Retrieved Nov 4, 2008, from http://www.investopedia.com/articles/06/CAPM.asp. 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