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Multiple Optima in Hoabinhian flaked stone artefact palaeoeconomics and palaeoecology at two archaeological sites in Northwest Thailand

2014-12-04T06:10:33Z

Student9215: Created page with "{{Summary |title=Multiple Optima in Hoabinhian flaked stone artefact palaeoeconomics and palaeoecology at two archaeological sites in Northwest Thailand |authors=Ben Marwick |..."

{{Summary
|title=Multiple Optima in Hoabinhian flaked stone artefact palaeoeconomics and palaeoecology at two archaeological sites in Northwest Thailand
|authors=Ben Marwick
|summary===Context:==
This article focused on using three models of human behavioral ecology (the Central Place Model, the Patch Choice Model, and the Optimal Dispersion Model) to determine how stone technology changed due to varying climate conditions. The two sites being compared are located in Thailand. The first is a rock shelter, Tham Lod, where the excavated site was 2x4 m and 450 cm deep, and the second is a rock shelter at Ban Rai, where the excavated area was 16 square meters but less deep than Tham Lod. The time periods that are being looked at is the late Pleistocene and early Holocene.

==Materials and Methods:==
The excavation found many flaked artifacts at both sites, which were used for determining adaptation processes due to changes in the environment. The environmental changes at the sites were recorded using freshwater shells, measuring oxygen isotope ratios.
One of the main focuses for this paper was predicting behavior based on the three different models: the Central Place Model, the Patch Choice Model, and the Optimal Dispersion Model. For the Central Place Model, there needed to be measurements of pre-processing. These were measured using ratios of MNF (Minimum Number of Flakes) to cores and by comparing the size distribution of flakes to the size distribution of flake scars on cores. Tham Lod was shown to have more evidence of pre-processing. The Patch Choice Model looked at each site and measured for every 100 years the rate of artifact discard per cubic meter. This allowed for making comparisons of habitation intensity between the two sites. Ban Rai showed higher habitation intensity. Finally, the Optimal Dispersion Model looked at how intensive an assemblage’s reductions was. The intensity was determined by looking at 5 flake variables. These variables were then compared with the oxygen isotope sequences. These results indicated that Tham Lod could have had variation in stone tools due to climate change, however, the results were not significant. The results are also unsubstantial at Ban Rai.

==Results:==
By using these ecological models, the results were inconclusive. The varying results from the three different models were unable to find a definitive connection between climate change and stone tool variability. Given these inconsistent results, the author looks to use multiple optima in order to modify the models to give a more dependable result.

|relevance=An important contribution that this author made in this article was this idea of multiple optima. The author used the human behavioral ecology models, but instead of using the traditional singular optima point, he applied the idea of multiple optima in order to understand better the results from the models.
|journal=Journal of Anthropological Archaeology
|pub_date=2013
|subject=Anthropology
}}

Technological Characterization of Lithic Waste-Flake Assemblages: Multivariate Analysis of Experimental and Archaeological Data

2014-11-20T01:10:53Z

Student9215: Created page with "{{Summary |title=Technological Characterization of Lithic Waste-Flake Assemblages: Multivariate Analysis of Experimental and Archaeological Data |authors=Robert J. Austin |sum..."

{{Summary
|title=Technological Characterization of Lithic Waste-Flake Assemblages: Multivariate Analysis of Experimental and Archaeological Data
|authors=Robert J. Austin
|summary='''Context:'''
This paper is looking into the Sullivan and Rozen typology. Sullivan and Rozen (1985), introduced typology, where sorting flake debitage into four different categories could help to decipher what kind of flake it came from: complete flake, broken flake, flake fragments, or no flake (debris). There has been criticism about this typology, but during this experiment, the author sorts assemblages using the Sullivan and Rozen typology to test the accuracy of this method.

'''Methods and Materials:'''
The experimental assemblage used in this experiment was derived from 15 replications. The results produced stemmed bifaces, unifaces, and halfted flake tools. Reduction strategies used a variety of methods, including both hard hammer and soft hammer percussion. The debitage was collected from each assemblage and bagged and labeled separately.
The flakes were subjected to discriminant analysis in order to evaluate objectively the Sullivan-Rozen typology. The assemblages were separated into three groups: patterned tool, large core, and small core based on prior criteria. It was hoped that the differences between the three groups would provide multivariate discrimination.
There was another test conducted to determine whether flakes from bipolar reduction strategies could be distinguished from the assemblages. A three group classification was applied in order to compare flake assemblages from patterned tool, conventional core, and bipolar core reduction.
The results from these reflected single assemblages. In an authentic archaeological site, assemblages may be mixed. So three simulated assemblages were created and subjected to discriminant analysis.

'''Results:'''
The results from the discriminant analysis were 86.67% accurately classified. The results from the final test were 95.83% accurate. And the simulated assemblages suggested that archaeological assemblages composed of a mix of flakes from patterned tool and core reduction strategies are likely to be classified as part of the patterned tool group if the core reduction debitage is 50% or less.
The accuracy of the analyses (86.67% and 95.83%) suggest that the Sullivan-Rozen typology is effective. However, the author notes that this study did not take into account nontechnological (such as trampling) factors that can alter the results of the Sullivan-Rozen typology, but this method can still be applied effectively in a preliminary fashion.

|relevance=The author here tests the ideas that Sullivan and Rozen put forth in their article Debitage Analysis and Archaeological Interpretation. However, their article sparked a fairly large debate among archaeologists and the typology was eventually deemed inadequate. Their ideas are still used today, but their exact methods and conclusions are not, which is something that the author of this article suggests. This debate, however, did emphasize the importance of examining flake debitage.
|journal=Lithic Technology
|pub_date=1999
}}

Is the Soanian techno-complex a Mode 1 or Mode 3 phenomenon? A morphometric assessment

2014-10-16T03:16:21Z

Student9215:

{{Summary
|title=Is the Soanian techno-complex a Mode 1 or Mode 3 phenomenon? A morphometric assessment
|authors=Stephen J. Lycett
|summary=

== Context ==
This paper looks at the Soanian techno-complex and discusses an experiment that aims to determine if Soanian technology is part of Mode 1 or Mode 3 technology. In the past, Soanian technology was associated with Mode 3 Levallois-style core reduction, but recently this association with Mode 3 tools has been ignored and Soanian technology has been associated with Mode 1 technology. The goal of this experiment is to confirm the presence of Mode 3 Levallois-style core reduction within Soanian technology. This is important so that we can accurately create a chronology of stone tools.

== Methods and Materials ==
This experiment was performed using data collected from Lower-Middle Paleolithic Old World nuclei representing 27 taxonomic units. These taxonomic units consisted of Mode 1 nuclei, Mode 2 hand axes, and Mode 3 Levallois core. The morphometric data of the total 564 nuclei that were collected was measured using a Crossbeam Co-ordinate Caliper, which provided 60 variables. Within the 564 nuclei, there were 11 nuclei that were termed ‘Soan?’ for the purpose of analysis.

The Discriminate Function Analysis (DFA) was used to sort the four groups (Mode 1, Mode 2, Mode 3 (Levallois), and Soan?). The DFA works by providing weightings that effectively categorizes the groups that have already been previously defined. With DFA it is possible to make two predictions with the results. The first prediction is that the ‘Soan?’ group centroid should be closer to the Mode 3 group centroid, and the second is that the ‘Soan?’ assemblage should overlap with variation. If both of these predictions are fulfilled, then the hypothesis can be confirmed. If one or neither are fulfilled, a second DFA is conducted where the taxonomic units are treated as 27 different groups. The results from the second DFA would confirm or reject the hypothesis.

== Results ==
The results of the first DFA fulfilled both the predictions. The ‘Soan?’ group’s centroid was closer with the Mode 3 group’s centroid than any other group. Thus showing that the Soanian techno-complex contains a Mode 3 Levallois core component. Even though the first DFA was successful, there was a second DFA performed, and it also confirmed the hypothesis. Although this experiment confirmed the hypothesis, the author notes that further research should be performed in order to clearly mark the chronology of these stone assemblages.

|journal=Journal of Archaeological Science, Volume 34, 1434-1440
|pub_date=2007
}}

Is the Soanian techno-complex a Mode 1 or Mode 3 phenomenon? A morphometric assessment

2014-10-15T14:47:33Z

Student9215: Created page with "{{Summary |title=Is the Soanian techno-complex a Mode 1 or Mode 3 phenomenon? A morphometric assessment |authors=Stephen J. Lycett |summary=This paper looks at the Soanian tec..."

{{Summary
|title=Is the Soanian techno-complex a Mode 1 or Mode 3 phenomenon? A morphometric assessment
|authors=Stephen J. Lycett
|summary=This paper looks at the Soanian techno-complex and discusses an experiment that aims to determine if Soanian technology is part of Mode 1 or Mode 3 technology. In the past, Soanian technology was associated with Mode 3 Levallois-style core reduction, but recently this association with Mode 3 tools has been ignored and Soanian technology has been associated with Mode 1 technology. The goal of this experiment is to confirm the presence of Mode 3 Levallois-style core reduction within Soanian technology. This is important so that we can accurately create a chronology of stone tools.

This experiment was performed using data collected from Lower-Middle Paleolithic Old World nuclei representing 27 taxonomic units. These taxonomic units consisted of Mode 1 nuclei, Mode 2 hand axes, and Mode 3 Levallois core. The morphometric data of the total 564 nuclei that were collected was measured using a Crossbeam Co-ordinate Caliper, which provided 60 variables. Within the 564 nuclei, there were 11 nuclei that were termed ‘Soan?’ for the purpose of analysis.

The Discriminate Function Analysis (DFA) was used to sort the four groups (Mode 1, Mode 2, Mode 3 (Levallois), and Soan?). The DFA works by providing weightings that effectively categorizes the groups that have already been previously defined. With DFA it is possible to make two predictions with the results. The first prediction is that the ‘Soan?’ group centroid should be closer to the Mode 3 group centroid, and the second is that the ‘Soan?’ assemblage should overlap with variation. If both of these predictions are fulfilled, then the hypothesis can be confirmed. If one or neither are fulfilled, a second DFA is conducted where the taxonomic units are treated as 27 different groups. The results from the second DFA would confirm or reject the hypothesis.

The results of the first DFA fulfilled both the predictions. The ‘Soan?’ group’s centroid was closer with the Mode 3 group’s centroid than any other group. Thus showing that the Soanian techno-complex contains a Mode 3 Levallois core component. Even though the first DFA was successful, there was a second DFA performed, and it also confirmed the hypothesis. Although this experiment confirmed the hypothesis, the author notes that further research should be performed in order to clearly mark the chronology of these stone assemblages.

|journal=Journal of Archaeological Science, Volume 34, 1434-1440
|pub_date=2007
}}

Me write pretty one day how to write a good scientific paper

2014-09-26T21:58:45Z

Student9215: Created page with "{{Summary |title=Me write pretty one day how to write a good scientific paper |authors=W.A. Wells |summary=Throughout this paper, the main points for writing a successful scie..."

{{Summary
|title=Me write pretty one day how to write a good scientific paper
|authors=W.A. Wells
|summary=Throughout this paper, the main points for writing a successful scientific paper are addressed. The main point that seems to be reiterated throughout the paper is the importance of reiterating your main point in your paper. It is okay to sound repetitive with your main point because, after all, it should be the message that you want your readers to walk away with after reading your paper. It is the one thing that you should keep consistent throughout each section of your paper. The reader wants to know how each step contributes to the main point.

Next, make sure you are being straight to the point. You don’t need to use filler words or extravagant vocabulary. Keep it simple. Make sure to read through your paper and take out any words or phrases that don’t serve a purpose. Either reword them or cut them out completely to make them simpler and to make your paper more direct. Typically, your readers won’t be experts in your topic, so you should keep right on topic and avoid wordy sentences.
Make sure to have a clear narrative to your paper. Your abstract is very important. You want to pack it full of information, include: background, a question, what was done, what was found, the conclusion/answer, and implications. After the abstract, make sure your paragraphs flow together. Don’t assume that your reader can connect your ideas and figure out why you are transitioning from topic to topic. Again, keep it simple.

Finally, be sure that you preview your conclusion. Don’t write the entire paper, slowly explain the process, what you have done and then finally state your conclusion. You shouldn't leave your reader guessing at what the conclusion of your paper is. Instead, you should let the reader know what your conclusion is ahead of time so that they are able to more easily follow along with your process.
}}