Post the prompt below just pick one question out of the three
1) Discuss three ways in which road construction and changes in Kohistani violence illustrate how culture is integrated. Be sure to define what “integrated” means (use definition given in class). In your discussion of change, you should consider factors that inhibited violence prior to the road’s construction, three changes that exacerbated violence after the road’s construction, and how these changes illustrate how culture is integrated.
2) Discuss how the work of Paul Farmer and the members of Partners in Health exemplifies the three fields of medical anthropology (ecological-epidemiological, critical, interpretivist). Be sure to define each of the three fields of medical anthropology and give specific examples of how Paul Farmer and Partners in Health implemented each. Your examples should describe things that Farmer/PIH actually did (their actions), not things about which they just thought, spoke, or wrote.
3) Discuss the quandry confronted by young people in many of the cultures that we studied this semester — whether and how to maintain their distinctive cultural identities in a rapidly changing, increasingly globalized world. Note that this is the question for which students in previous semesters have had the most difficulty. Here’s what you should NOT do — go through several cases and talk about how globalization is affecting them. Rather, imagine yourself as a young person in a culture that is being affected by globalization. What forces (e.g., old and new) would be pulling on you as you tried to define your own identity in a changing world?
Sample Solution
xtracted for the period from 1999 to 2017 containing over 34 m illion observations. to begin, only common inventory observations are maintained in the query to enhance the publish-merger data compatibility with the IBES rate goal dataset. For common stock the variable percentage code amounts to either 10 or 11, consequently handiest those share codes are kept inside the pattern. moreover, tickers with multiple unique stocks are dropped as those are not properly similar to the IBES identifiers so that it will be elaborated on later. moreover, a .TXT record such as the last agency ticker identifiers is derived from the dataset within Stata in order to simplify extraction of successive queries within WRDS as simplest data on the ones predetermined businesses may be withdrawn from WRDS hence miserable the record size. in the each day inventory charge query the actual rate, bid, ask and shares first-rate are adjusted using the so-known as adjustment elements if you want to make the referred to variables comparable over the whole 1999-2017 length. those adjustment factors are built via CRSP and regulate for company moves consisting of inventory splits, dividends and rights offerings. moreover, the effective spread variable is created in addition to Hendershott et al. (2011) via taking the difference among the final bid and ask its midpoint and the actual transaction rate of that day as well as a volatility variable this is calculated as the deviation amid the every day high and the every day low. IBES â fee goal IBES additionally known as the Institutional brokersâ Estimate gadget is a Thomson Reutersâ database which holds historic analyst estimates for extra than twenty forecast measures including profits per proportion, revenue, price targets, purchase-maintain-promote recommendations and gross income regarding over 60,000 organizations. After finishing the extraction of fee target estimation facts which include their horizon and analyst name records from WRDS using the equal 1995-2017 duration as used before, it become found that the IBES statistics couldn’t without delay be merged with the CRSP information. concerning IBES, it contains ticker variables and simply the variable legitimate ticker is like minded with the ticker variable in CRSP and ought to no longer be stressed with âtickerâ in the IBES dataset.as a result, âofticâ is changed to its CRSP name: ticker. additionally, it ought to be mentioned that the in IBES so referred to as âannouncement dateâ have to be the leading date. in the end, price goal estimation values are matched with their respective destiny actual price through lagging the forecast with its horizon that means that an estimation with a horizon of 6 months is lagged 6 months. Federal Reserve bank â hobby costs The WRDS fees database used on this research is based totally upon the Federal Reserve Boardâs H.15 release that consists of selected interest fees for U.S. Treasuries and personal cash market and capital marketplace units. each day charges are per commercial enterprise day and said in annual phrases. To encompass interest charges as a controlling aspect inside the regressions, the prices of U.S. treasury payments with a maturity of 3 months are extracted from the WRDS costs database for the duration 1995 to 2017. The prices are merged with the grasp dataset the usage of date because the common variable.>
xtracted for the period from 1999 to 2017 containing over 34 m illion observations. to begin, only common inventory observations are maintained in the query to enhance the publish-merger data compatibility with the IBES rate goal dataset. For common stock the variable percentage code amounts to either 10 or 11, consequently handiest those share codes are kept inside the pattern. moreover, tickers with multiple unique stocks are dropped as those are not properly similar to the IBES identifiers so that it will be elaborated on later. moreover, a .TXT record such as the last agency ticker identifiers is derived from the dataset within Stata in order to simplify extraction of successive queries within WRDS as simplest data on the ones predetermined businesses may be withdrawn from WRDS hence miserable the record size. in the each day inventory charge query the actual rate, bid, ask and shares first-rate are adjusted using the so-known as adjustment elements if you want to make the referred to variables comparable over the whole 1999-2017 length. those adjustment factors are built via CRSP and regulate for company moves consisting of inventory splits, dividends and rights offerings. moreover, the effective spread variable is created in addition to Hendershott et al. (2011) via taking the difference among the final bid and ask its midpoint and the actual transaction rate of that day as well as a volatility variable this is calculated as the deviation amid the every day high and the every day low. IBES â fee goal IBES additionally known as the Institutional brokersâ Estimate gadget is a Thomson Reutersâ database which holds historic analyst estimates for extra than twenty forecast measures including profits per proportion, revenue, price targets, purchase-maintain-promote recommendations and gross income regarding over 60,000 organizations. After finishing the extraction of fee target estimation facts which include their horizon and analyst name records from WRDS using the equal 1995-2017 duration as used before, it become found that the IBES statistics couldn’t without delay be merged with the CRSP information. concerning IBES, it contains ticker variables and simply the variable legitimate ticker is like minded with the ticker variable in CRSP and ought to no longer be stressed with âtickerâ in the IBES dataset.as a result, âofticâ is changed to its CRSP name: ticker. additionally, it ought to be mentioned that the in IBES so referred to as âannouncement dateâ have to be the leading date. in the end, price goal estimation values are matched with their respective destiny actual price through lagging the forecast with its horizon that means that an estimation with a horizon of 6 months is lagged 6 months. Federal Reserve bank â hobby costs The WRDS fees database used on this research is based totally upon the Federal Reserve Boardâs H.15 release that consists of selected interest fees for U.S. Treasuries and personal cash market and capital marketplace units. each day charges are per commercial enterprise day and said in annual phrases. To encompass interest charges as a controlling aspect inside the regressions, the prices of U.S. treasury payments with a maturity of 3 months are extracted from the WRDS costs database for the duration 1995 to 2017. The prices are merged with the grasp dataset the usage of date because the common variable.>
