代写ENVIR301 Data Mining & Census Records代写C/C++程序

Data Mining & Census Records

In today’s lab, we will consider the socio-economic and political dimensions of the Northern Spotted Owl “controversy.” The in-class and post-lab components are all contained on this one handout.

With the listing of the Northern Spotted Owl as a Federally Threatened Species, and the passage of the Northwest Forest Plan in 1994, the timber industry argued that a moratorium on logging in old growth forests would have adverse effects on rural communities dependent on timber. These included a number of primary effects, including lost jobs and income, and a number of dramatic secondary effects, including “increased rates of domestic disputes, divorce, acts of violence, delinquency, vandalism, suicide, alcoholism, and other problems,” that the timber lobby predicted might follow from lost jobs and income.

This week in lab we will “mine” data publicly available through the U.S. Census Website (and related websites) to investigate how one timber-dependent community, Forks, WA (on the Olympic Peninsula), may have been impacted by the ban on old growth logging put into place by the 1994 Northwest Forest Plan (which applied to all of western Washington, including east slope of the Cascades).

The learning goals for this week’s section activity are as follows:

1. To generate and test hypotheses related to the possible socio-economic effects of a major change in environmental policy (i.e., the Northwest Forest Plan) on a timber-dependent community. You could apply these same concepts to analyze the impacts of a change in any policy on any number of other kinds of relevant communities.

2. To understand the use of indicators to analyze an abstract concept like Socio-Economic Well-Being (SEWB).  

3. To understand the benefits and drawbacks of data mining – using one or more sources of data collected for another purpose to test a hypothesis or answer a question related to your own research.

4. To gain expertise in accessing and analyzing data available on the U.S. Census Website. This is a fantastic repository of publicly available data that you may choose to draw on during your capstone research projects. And note that these data can be housed in other places too, which may have more user-friendly interfaces, e.g. www.ofm.wa.gov, https://www.ipums.org/.

5. To better understand the concept of a control group.

6. To understand how the concept of Diversity, using Simpson’s Index (which we used in an ecological context in the last lab), can be applied to employment diversity.

Sources and Inspiration:

Donoghue, E. and Sutton, N. (2006) Socioeconomic Change in Planning Provinces of the Northwest Forest Plan Region. Northwest Science 80 (2): 73-85
https://www.fs.usda.gov/research/treesearch/27205

Sarathy, B. (2006) The Latinization of forest management work in southern Oregon: A case from the Rogue Valley, Journal of Forestry 104:359-65.

Lab Procedure

We will test the hypothesis that the ratification of the 1994 NW Forest Plan caused a decline in socio economic well-being (SEWB) in Washington timber communities. In this lab, one of the towns you will use as a test case is Forks on the Olympic Peninsula (they once called themselves the “Timber Capital of the World”).  

Step 1) With your classmates, brainstorm a list of factors that might be associated with SEWB. In other words, how would one “operationalize” the concept of SEWB?

Step 2) Now, with your classmates, how do you predict that these factors should change before and after the NW Forest Plan.

Step 3) Talk to each other about an ideal experimental design for addressing the hypothesis above. Will you need to sample more communities? If so, why? And which? Try to be specific. Hint: Forks is a timber dependent community within the region affected by the NW Forest Plan.

Post-Lab (Part 1):

Now that you’ve thought about what you need to do, work in small groups to test the hypothesis above. You must work with at least 2 communities. Forks, WA will be one of them.

Question 1: How do you predict that these factors should change before and after the NW Forest Plan? Complete this table with your predictions (higher or lower), in each cell, and label Town B with an actual name. Researchers often fill out tables like this, prior to collecting data. You could also sketch out graphs if you wanted to.

To access census data for Forks, WA (and other communities of your choosing), first go to www.ofm.wa.gov.  Click on “Washington Data and Research” in the top bar. Then go to “Decennial Census Data”. Click on 1990. Scroll down to Forks, WA. Click on the link and download the zip folder.

Now go to 2000. Scroll down and click on the “4 page demographic profiles” for WA state. Scroll down to the data for Forks city, WA. Open the pdf which contains tables DP-1 through DP-4. These data should be comparable to what you just opened for 1990.

Test the above hypothesis for Forks, WA, looking at SEWB in five different ways. Make sure you display your data as clearly as possible. If you need to do any small calculations on the census data before you present the data, you should do so. Make sure you consider your experimental design discussion from earlier, and include data from at least one additional population besides Forks. Note that when looking at income, you should consider adjusting for inflation using this tool: https://www.bls.gov/data/inflation_calculator.htm

Question 2: Complete this table with resulting values in each cell. Replace Town B with an actual town.

Question 3: From your data analysis, did the 1994 NW Forest Plan likely cause a decline in socio economic well-being (SEWB) in Washington timber communities? Please elaborate on your results in a paragraph, using complete sentences.

Post-Lab (Part 2):

Question 4: Brinda Sarathy suggests that demographics of people employed in forestry have shifted from white to Latino. Do you have any sense of whether this might be true in Forks, WA? Support your argument with data in the format of a table, again using a control community. You will likely want to look at 2-3 variables (including a demographic control) to address this hypothesis. What are they and why did you choose these variables?

Question 5: Discuss the results: If you supported the hypothesis, are there any limitations to your ability to confidently make this argument with the data at hand, of if you rejected the hypothesis, what are some reasons why that might be?