Soil Mechanics (Geotechnics Essay Example | Topics and Well Written Essays - 1000 words

Soil Mechanics (Geotechnics - Essay Example Soil is composed of particles such as silt, clay, gravel and sand and they can also contain other gases that exist in between these particles. The study of soil is very important because this is what makes the study of geotechnical engineering possible. This is a subtopic in civil engineering and it is a very complex topic. Soil mechanics is applicable in many ways as far as building and construction is concerned and some of the best examples are such as building foundations of bridges, dams and sustaining systems of buried pipelines. This is very important because it ensures that buildings do not fall apart easily in the modern world and this contributes a lot to the development of different cities world wide. The study of soils is also very important because it contributes a lot to good agricultural products. Many areas of engineering depend on soil mechanics and some of these areas are such as coastal engineering, geophysical engineering and hydrology among other areas. One of the best ways of approaching the topic on geotechnics and drainage is through understanding the composition and genesis of soils. This is one of the best examples of a diagram that clearly defines the formation of soils as far as volumes of water, air and solid is concerned. The V?, V?, and Vs represent the amount of solids, air and water present in a specific mixture of soil. W?, W?, and Ws in the diagram above stand for the weights of solids, air and water within a soil mixture and M?, M?, and Ms stand for the masses of water, solids and air found in a mixture of soil. The formulae for calculating the weights of all the named particles present is Mass multiplied by the acceleration of gravity which is; Ws=Mg. Types of Triaxial Tests There are several types of triaxial tests but the most common ones are; Consolidated Drained also known a CD, Consolidated Undrained tests which is also referred to as UD and Unconsolidated Undrained. In the consolidated drained or CD, the test is done th rough consolidating and shearing while compressing it with the drainage. In the second type of test, the sample is not drained and in the third type of test, the sample is constantly compressed. This is an example of soil horizons from www.wikipedia.com . A; can be referred to as the colluviums or top soil, B; is the Residual soil that is mature and C; is weathered rock. In most cases, soil deposits become affected by how they are transported to the specific location where they can be found. Understanding the formation and deposition of soils makes it quite easier and understandable especially when it comes to dealing with geotechnics calculations. Clay is composed of several minerals that form structures that look like a sheet which have a length range of 10 x 10 ?7 and 4 x 10?5 and its thickness ranges from 9 x 10?9 and 2x 10?6 and their surface area is large. Through understanding the formation of soils, one can easily understand how different stresses and shears are formed in di fferent phases on a normal circumstance and all this is part of the study of geotechnics (Chen 2010). Stress strain curve diagram. Looking at the curve above, one can easily predict the stability of the soil by measuring the shear strain against its shear strength Cell pressure kN/m2 Deviator stress kN/m2 kN/m2 2 (a). Normal and Over- Consolidated Stratum Normally consolidated stratum is one which is very dense and packed tightly as one goes deep the strata. An over-consolidated clay stratum is one which occurs when water is squeezed out of the ground with

Witchcraft and Violence in the World Today Essay

Witchcraft and Violence in the World Today - Essay Example As history has shown, fear is a powerful motivator. Perhaps the most well-known example in the United States would be the Salem witch trials in seventeenth-century Massachusetts. This type of violence, often driven by personal vengeance or mass hysteria, can still be found in the world today, and in fact, there are many examples of just such a fear of the unknown causing people to lash out against their neighbors. In the modern world there are several different definitions for the term â€Å"witchcraft.† Stephen Hayes provides an excellent analysis of the problems associated with the terminology as it is used by various people around the world. According to Hayes, many people use the word witchcraft in a traditional manner. To these people using witchcraft means to use dark or black magic to cause harm to others. In essence, these people see the use of witchcraft as evil. In contrast, many followers of the neopagan religion Wicca use the term witchcraft synonymously for their religion. To Wiccans there is nothing evil about the term, save for the violence that was committed against alleged witches throughout history. This paper will use the more traditional definition of witchcraft. The reasoning for this choice can best be summarized by Hayes: â€Å"In normal, non-Wiccan usage †¦ the essence of witchcraft and sorcery is the causing of harm to persons or property by invisible occult means† (339). Tanzania is a country in eastern Africa lying on the Indian Ocean. The majority of the population in this country believes in witchcraft, similar to the beliefs in many other areas of Africa. Elderly women in Tanzania are often accused of witchcraft and murdered. Additionally, according to some researchers, in years when Tanzania suffers unusual rainfall either by drought or flooding then the murders of accused witches double (Kristof, par. 3). However, weather is not the only cause for these murders. Many of the murders are also performed at the beh est of traditional healers who blame the elderly women of performing witchcraft to cause illness in their patients (Dickinson, par. 2). Clearly the murders in Tanzania have many different causes at their roots. Other areas of Africa also have problems with violence against those accused of witchcraft. The Democratic Republic of Congo is located in western central Africa. It, like its eastern neighbor Tanzania, also has problems with attacks on â€Å"witches.† In 2008 there was a massive scare in the country surrounding purported thefts of men’s penises. Several cases of attempted lynching occurred during the incident in which suspected sorcerers were â€Å"accused of using black magic to steal or shrink men’s penises† (Bavier, par. 1). Police in Kinshasa arrested the accused witches as well as their alleged victims in order to avoid the murders associated with a similar incident a decade earlier in Ghana, another African country. The continent of Africa i s not the only place in the world where violence occurs against those who purportedly practice witchcraft. According to Tess Eastman, a woman in India was recently tied to a tree and beaten for being a witch (par. 1). The violence in this case was initiated by a man who had admitted to hiring the woman to heal his wife with magic and prayer. However, the man subsequently accused the woman of witchcraft when his wife’s condition worsened. This accusation was enough for the violence to happen. The attack, while not fatal for the accused witch, was violent enough to result in the arrest of six people, including the original hirer of the woman. While it would be tempting to believe that violence against accused witches only happens halfway around the world from the United States,

Macbeth’s Gender Role Reversal Essay Example for Free

Macbeth’s Gender Role Reversal Essay William Shakespeare’s tragedy â€Å"Macbeth† completely challenges the idea of traditional gender roles and social norms during the renaissance period. The male characters have many feminine traits while the female characters have many more masculine and manlier traits. This was going entirely against the stereotypical outlook of the roles you’re supposed to play as your gender during that time of history. During the renaissance period women were only expected to clean, cook, and to have babies. Men on the other hand were typically expected to work hard and to provide for the home. Socially women didn’t have power or respect and men were the ones who were supposed to be brave and tough at the best of times and the worst of times. That idea is challenged many times throughout Macbeth as their are several examples where Lady Macbeth remains strong while Macbeth crumbles and becomes weak. The play consistently challenges the society norms of gender roles. It’s obvious the Macbeth’s don’t serve as your stereotypical husband and wife. Right away throughout the first couple of acts, Shakespeare introduces Lady Macbeth’s character as an assertive and dominant woman that makes the decisions over her husband Macbeth. Lady Macbeth really makes it apparent that she wears the pants in there relationship. For example, in scene 1 act 5 when Macbeth tells Lady Macbeth King Duncan is coming and he seems to be very hesitant on how he will handle the King’s presence. Lady Macbeth takes charge and asserts her dominance by saying, â€Å"He that’s coming/ Must be provided for, and you shall put/ This night’s great business into my dispatch† (scene 1 act 5 64-66).In traditional society, if the king is coming to your house, it would be very unusual for the lady of the house to be in charge of handling the appearance by the king. Lady Macbeth and Macbeth also exchange roles in the way they handle their emotions and the way they handle the guilt. For instance, when it comes to the thought of murder and death, Lady Macbeth shows no mercy, and when King Duncan was murdered, she remained unphased by the act. This is apparent when she deals with Macbeth leaving the gory daggers at the site of the murder, â€Å"Give me the daggers. The sleeping and the dead/ Are but as pictures; ‘tis the eye of childhood/ That fears a painted devil.†(scene 2 act 2 56-58). Macbeth is portrayed as emotionally unstable and soft as he is afraid to even go back into the room where the murder took place, â€Å"I’ll go no more/ I am afraid to think what I have done†(scene 2 act 2 54-55). This interaction between Macbeth and Lady Macbeth really shows the unusual roles one another play in their relationship because, in a situation where someone is murdered or there is a serious crime, women aren’t usually t he ones who are brave and strong-minded about it, men are. As the play goes on, Lady Macbeth begins to lose her fierce and intimidating persona as Macbeth becomes the more assertive and dominant one. Lady Macbeth starts losing her edge when it becomes less difficult to get Macbeth to follow through with his murderous acts. Anytime Macbeth thinks you’re interfering with his kinship, he’ll have no problem taking you down and getting you out of his way. Macbeth no longer needs Lady Macbeth to persuade him. This is very apparent when he shows no mercy planning the murder of Banquo, â€Å"There’s comfort yet, they are assailable/ Then be thou jocund: ere the bat hath flown/ His cloistered flight, ere to black Hecate’s summons/ The shard-borne beetle with his drowsy hums/ Hath rung night’s yawning peal, there shall be done/ A deed of dreadful note† (scene 3 act 2 40-44). A completely different Macbeth we see out of this quote, no longer hesitant and no longer appearing to be affected by guilt. Now that Macbeth is this individual who is ready and eager to kill, Lady Macbeth begins to show the side of her that wasn’t present at the beginning of the play, â€Å"Come on. Gentle my lord/ Sleek o’er your rugged looks, be bright and jovial/ Among your guests tonight† (act 3 scene 2 26-28). Lady Macbeth expresses emotion and traits of care, unlike any other time. The play Macbeth features many different gender reversals throughout the entire play. Shakespeare really tests the normality of having women be the assertive and dominant one in a marriage while having the man be kind of timid and soft. Lady Macbeth and Macbeth’s gender reversals distinctively show the extreme traits one another possess and it gives an opposite perspective than what we are used to. Whatever goes up always must come down, and when Lady Macbeth and Macbeth begin to form into traditional gender roles, that becomes the start of their decline.

Evolution of Mobile Device Technology

Evolution of Mobile Device Technology Introduction Since the revolution of the smartphone in 2005 the development progress in this field grows rapidly. It became a part of our life and played a big role to change the attitude of our life style. This technology (smartphone) didnt stop at that level but it spread everywhere to cover all sides of our daily activities. Even anew terminology appear to name this technology is Internet of Things (IoT) where this concept describe any device connected to the internet. All this technology convert our life to something called smart, so nowadays we have smartphones, smart home, smart car ext. These smart devices facilitate our daily tasks where no need to set on the front of the computer or trying to find an open Wi-Fi because you are expecting an important email you dont know when it will be delivered to your inbox. This technology gave the people almost everything they need which has made people ask for more and it became their partner or even addicted. Day by day people relay more and more on the smart technology and they share all information even sometimes the secrets. This information start attract some people for any reason either to sell this information to third party or to blackmail their victim. This bring a new challenge to everybody in the society and there are a new cases daily because of the smart devices. The device can be a tool to attack the victim data or it found in the crime scene in both scenarios can be consider an evidence. Mobile device technology The mobile devices evolution is linked to the mobile technology where each one effect on the other one. Because the mobile device technology required a specific features. First Generation By looking to the first generation and list its features we can guess what kind of mobile device technology can be used in that period. According to (Agrawal, 2015)] the first generation was analog it was introduced in 1980. The technical specification was not that much where they focused on produce a mobile phone. The main feature of 1G mobile Speed up to 2.4 kbps so it was used for calling only It use analog signals (analog telecommunications standards) Poor voice quality Poor battery life Limited capacity No security Focusing on the last two points because they are related to the research paper. Regarding the security at that time 1G does not support the encryption. The security was limited where some phones (e.g. Mitsubishi MT-7) in 1993 has a pin code only. The memory as well didnt get that much attention, but later on in 1989 Motorola (8900X-2) add a small volume of memory which can store 20 telephone numbers in the address book. This generation is limited in everything even in the forensics user couldnt do bad things with it just verbally. Feature phones and smartphones From second generation the improvement obviously in the mobile device technology. (Qualcumm, 2014) Show the evolution on theses generations used digital signal compare to the first generation. This change took the mobile devices technology ahead with new features the users didnt experience them before in the previous versions of 1G mobile devices. In these generations there are basic features with different specifications. The diagram (DAS, 2015) show the different parts of the mobile phone. As the diagram shows the mobile device component, most mobile devices have a common hardware component (GSM Mobile Phone, n.d.), consist of microprocessor, a radio module, read only memory (ROM), a microphone and speaker, random access memory (RAM), a digital signal processor, a variation of hardware keys and interfaces and display screen. The operating system (OS) of a mobile device may be stored in either NAND or NOR memory while code execution normally happens in RAM. The general changes in the mobile devices is the size (capacity, screen) and the speed as well the quality of the display, but some time do any change in the phone means change the component chips used. This changes can lead to another technology. Overview of the feature phone and smartphone Feature phone Smartphone Processor Limited speed(~52Mhz) More speed(~1GHz dual-core) Memory Limited capacity(~5MB) Large capacity(~128GB) Data transmission Speed 64-144 kbps 300 mbps Display Small size color, 4k -260k (12-bit to 18-bit) Large size color, 16.7 million (~24-bit) Card slot None, MicroSD MicroSDXC Camera Still, Video Still, Panoramic, and Video(HD) Text input Numeric Keypad, QWERTY-style keyboard Touch Screen, Handwriting Recognition, QWERTY-style keyboard Voice input None Voice Recognition (Dialing and Control) Cell interface Voice and Limited Data Voice and High Speed Data transfer (4G and LTE) Positioning None, GPS receive GPS receive Wireless IrDA, Bluetooth Bluetooth, Wi-Fi, and NFC Battery Fixed/Removable, Rechargeable Li-Ion Polymer Fixed/Removable, Rechargeable Li-Ion Polymer Feature phone and smartphone has common facility, but the capability is much different. Where both types of phone support SMS (text messaging), voice and personal information management such as phonebook and calendar. Smartphone has a better capabilities and larger then feature phone where it support better screen resolution and have integrated keyboard or touch screen. Smartphones act as a small PC and support wide range of applications. There are many operating system (OS) (Guru, 2015) in the market for the smartphone the top OS popular are Symbian (Nokia), Android (Google), Apple IOS, Blackberry (RIM), Windows (Microsoft) and BADA (Samsung). These operating system support multi-tasking and designed to match the user requirements for a high end mobile device. Feature phones has a closed operating system, so the supported applications, games, personal information management and chat are limited. Memory Mobile devices contain two types of memories. The first type is volatile memory and the second one is none-volatile both of them work side by side. The volatile memory (RAM) is used for code execution. This type of memory is effected by the power, so if the power goes off RAM is lose all contents. The second type is non-volatile memory the contents are not effected when the power goes off. The main technologies for non-volatile flash memories are NOR and NAND. NOR memory first introduced in 1988 by Intel. In 1989 Toshiba introduced the NAND flash technology which has many benefits over NOR memory. NOR came to replace ROM with EPROM and EEPROM. The most advantage of NOR is the reading speed faster than NAND. In the other hand NAND has many features which is not applicable for NOR. These are the general difference between NAND and NOR NOR reads slightly faster than NAND. NAND writes faster than NOR. NAND erases data much faster than NOR. NAND has smaller erase units, so less erases are needed. There are different types of NAND memories but the paper focusing on the EMMC and UFS. EMMC stand for embedded multimedia card this chip is an advanced managed memory. According to (Samsung, 2013) it is widely used in phones, cameras, GPS and smart TV. It helps the designer to save time and make the product thinner. Also it enhanced the storage capacities and speed. One of the advantage of EMMC reduced the development time and control cost. The NAND memories before EMMC required changes either in the chipset or the OS. EMMC is a half-duplex because the interface is parallel so it will be read or write. UFS Mobile devices growth rapidly last few years this bring a challenge to the manufacturer to add memory that (Toshiba, 2015) will have a high bandwidth, high capacity, low power consumption and low cost. These factors were very important to improve the mobile devices. Because adding ordinary extra memory it will increase the cost of all mentioned factors. In 2014 Samsung announce about the new memory which meet the requirements of the four factors of the manufacturer. Universal flash storage (UFS) was built specially for mobile devices which required low power and at same time provide high performance. UFS is a full duplex because it has serial interface read and write done separately. The image below (BHATT, 2014) shows the advantage of UFS over EMMC Challenges according to (Zareen, 2010): The major challenges in mobile forensics are: The changes in the architecture of the new released of mobile devices, where the examiner has to be up to date and do more tests to be sure he can do data extraction. The new mobile devices it has the ability to encrypt the date this can be a big challenge to the examiner. Hardware differences there are different brand and model of mobile devices in the market the examiner has to come across as much as can of brands and model to be familiar about the technology. Lack of resources the rapid growth of mobile devices required new tools and acquisition accessories. Anti-forensic techniques make the investigation more difficult, as an example data hiding, data obfuscation, data forgery, and secure wiping. Passcode recovery the examiner has to work carefully to access the device without damaging the data. Malicious programs can be a challenge to the examiner it may attempt to spread to other devices over the wired interface or a wireless. Safety the examiner life can be on danger, the device can contain different kind of risk on the examiner life. The device may contain a biology or chemical hazards which will impact on the examiner. Data acquire process Capability Logical extraction, file system and physical extraction normally done by software. Even the locked mobile devices and with passkey can be unlocked using software. Not all mobile devices support the same process of data acquisition. Joint Test Action Group (JTAG) support in-system (ISP) programming and reading. It is an advanced hardware level data acquisition in the physical extraction stage. It depend on the Test Access Ports (TAPs) of the device and instructing the processor to transfer the raw data stored on connected memory chips. If the memory support JTAG then the TAP can be addressed of the memory through the JTAG interface. All memory address goes the though the data bus and it can be read by shifting the boundary-scan register value through JTAG chain. In this way the entire memory content can be read by find the memory address. The entire memory can be copied in this way. If the memory doesnt support the JTAG then it can connect to TAP of another device this could be the processor. The processor has direct access to the memory through the system bus. By connecting to CPU TAP the memory can be read. Steps of JTAG according to (Elder, n.d.) Identify TAPs by researching the forums and related websites as well documented devices. If the TAPs cannot be identified then check the device PCB for possible TAPs and trace it manually to find appropriate connector pins. Solder wires to the pinout in the mobile device. Connect the other side of the wires to JTAG emulator (RIFF box, volcano, ATF nitro). Select the memory sitting than read the flash memory. Analyze the data with the forensics tools. Chip-off Chip-off forensics is the next level if the JTAG method not work properly to extract data. This level involve physically remove the flash memory to extract the data from the mobile device then acquiring the raw data using specialized equipment. This way is powerful where it can be used to collect all data from the memory even if the device is damaged jut memory must be in a good condition. The examiner must pay attention to highest temperature can apply the chip to remove before it get damage. According to Samsung the temperature range of EMMC used in mobile devices are -25ÂÂ °C ~ 85ÂÂ °C. Remove the memory (de-soldering) chip using appropriate heat (-25ÂÂ °C ~ 85ÂÂ °C) always the examiner must monitor the temperature to be within the range. Clean the chip carefully to remove the comical suck on the chip memory. Use special chip programmer and adapter to acquire the data from a variety of flash memory (UP-828P Programmer). Analyze the data with the forensics tools. Samsung T479 Gravity 3 feature phone Manual extraction if the device is on and unlocked Isolate from the network Check battery status Check device status Record date and time Browse the device content using keypad or touch screen If the device powered off or locked Isolate from the network Check device status Turn on the device If not start try to charge it If cant be charge stop proceed If the device start but it is locked stop process Challenges Deleted data cant be retrieve because no tools used to extract data in this stage. Error may accrued. Browse the device it can be difficult because broken buttons or touch screen problem. Tools used to record the evidences. Ramseys STE3000FAV Project-A-Phone Logical extraction This stage required special software to extract data from the device. If the device is on and unlocked Isolate form the network (disable Wi-Fi and hotspot, airplane mod) Check the status of the device Document what on the screen and the apps running in the background Enable USB debugging and stay awake Check memory card availability If available copy card Create hash value Reinstall copied memory Connect mobile to PC has software to extract data List of data can be get in logical extraction Phone book Call Logs SMS Calendar MMS ESN/IMEI Pictures Videos Ringtones Audio/Music Memory Card If the device is locked connect to a PC has software to break lock (most of forensic tools) follow steps in 1 Tools used in this stage UFED 4PC, Oxygen and Xry (SIM call not supported) Challenges Cant retrieve deleted data File system If the device is on and unlocked Same procedure as logical extraction List of data can be get in logical extraction Extract user lock Files Decoding File System Reconstruction Bookmarks Calls Contacts Installed Applications MMS Notes SMS Web History Tools used in this stage UFED 4PC, Oxygen and Xry (SIM call not supported) Challenges Physical Extraction This phone doesnt support physical extraction. JTAG This phone support JTAG Samsung I9500 Galaxy S4 motherboard Mobile device Process Samsung T479 Gravity 3 Samsung I9500 Galaxy S4 Manual extraction Yes Yes Logical extraction Yes Yes File system extraction Yes Yes Physical extraction No Yes JTAG Yes Yes Chip-off Yes Internet of thing overview Internet of things (IOT) refer to any physical device which can have an IP address and connected to the internet. According (Fremantle, 2015) the IOT come to facilitate people life and make it easier. It will touch every aspect of our lives, including our houses, work places, transportation and even our bodies. This new technology make humans overcomes the location obstacle between people and the machine enabling them to communicate and interact intelligently. Rapid growth of Information Technology already allowed Internet of Things to start to be as a reality in recent days. If we look around us, we already started to see and touch the smart phones, home automation, smart traffic lights, smart sensor devices at industrial locations, Health services, Radars, Environment Researches, and many other sectors. Definitely, the future of IoT will be full of surprises and new unexpected and unpredictable technologies might be introduced. IoT technology is significantly growing at a critically dangerous pace and Information Technology Researchers predict that by the year 2020, 10th of billions of wireless devices will be connected wirelessly as part of the IoT industry. People will be able to do unimaginable things remotely in an unbelievable time and it is expected that almost anything might be connectable. According to (Lobaccaro, 2016) there are four categories: 1. Integrated wireless technology (IWT); 2. Home energy management system (HEMS); 3. Smart home micro-computers (SHMC); 4. Home automation (SHS/HA). Agrawal, J. (2015). Evolution of Mobile Communication Network: from 1G to 4G. BHATT, B. (2014, 4 13). Universal Flash Storage. Retrieved from Slideshare: https://www.slideshare.net/BhaumikBhatt4/universal-flash-storage DAS, S. (2015, 8 18). Parts of a Mobile Cell Phone and Their Function. Retrieved from http://www.mobilecellphonerepairing.com/parts-of-a-mobile-cell-phone-and-their-function-big-parts.html Elder, B. (n.d.). Chip-Off and JTAG Analysis. Retrieved from Evidence: http://www.evidencemagazine.com/index.php?option=com_contenttask=viewid=922 Fremantle, P. (2015). A REFERENCE ARCHITECTURE FOR THE INTERNET OF THINGS. GSM Mobile Phone. (n.d.). Retrieved from RF Wireless World: http://www.rfwireless-world.com/Articles/gsm-mobile-phone-basics.html Guru. (2015, 10 28). Top 10 Mobile Phones Operating Systems. Retrieved from shout me: https://www.shoutmeloud.com/top-mobile-os-overview.html Qualcumm. (2014). The Evolution of Mobile. Samsung. (2013). Samsung Smart Memory. Samsung. Toshiba. (2015). UFS memory. Toshiba. Zareen, A. (2010). Mobile Phone Forensics Challenges. http://forum.gsmhosting.com/vbb/f672/guide-how-find-direct-EMMC-pinout-step-step-pictures-1724774/ https://www.oxygen-forensic.com/download/articles/Oxygen_Forensic_Detective_Getting_started.pdf https://blog.elcomsoft.com/2016/01/forensic-acquisition-android/ http://www.bulleproof.com/Papers/Android%20Forensics%20Techniques.pdf https://blog.elcomsoft.com/2016/01/forensic-acquisition-android/ https://www.hackingloops.com/android-forensics-tutorial-4-unlock-android-pattern-lock/ http://resources.infosecinstitute.com/android-forensic-logical-acquisition/#gref https://www.gillware.com/forensics/blog/digital-forensics-case-study/forensic-case-files-htc-one-chip-off https://digital-forensics.sans.org/media/DFIR-Smartphone-Forensics-Poster.pdf http://www.gsmarena.com/samsung_t479_gravity_3-3335.php http://www.riffbox.org/jtag-news/riff-jtag-samsung-gravity-3-sght479-unbrick-dead-boot-repair-supported/

Writing Styles in the Puritan Time Period :: essays research papers

In American Literature, the period of the Puritans sticks out as a time with many great authors. Two, William Bradford and Reverend Jonathan Edwards are still studied today. Bradford was an author who wrote about the historical section of Puritan life, while Edwards was a great speaker who wrote sermons to give in front of his congregation. Although living in the same time period Reverend Jonathan Edwards and William Bradford used very different styles of writing. In writing, praise and everyday living the Puritans favored the ordinary and simple. William Bradford wrote in what is considered the 'plain style.' This form of writing was used by many Puritan authors and was thought to be direct and to the point. The plain style consisted of simple sentences and everyday used language. It never had figures of speech and especially not any imagery. A good example of this style is found in the passage from Bradford's Of Plymouth Plantation, "They began now to gather in the small harvest they had, and to fit up their houses against winter, being all well recovered in health and strength and had all things in good plenty." William took this otherwise exciting story of the Puritans first winter and wrapped it all into one monotonous sentence. Bradford's word choice epitomized the 'plain style' and that was all the Puritan society would read or hear until Jonathan Edwards. The Reverend Jonathan Edwards chose a style expressing his concerns much more creatively than his fellow Puritan authors. Jonathan's style was almost the complete opposite than the 'plain style.' He used many figures of speech and metaphors. An example of one of these fiery metaphors is from his speech, Sinners in the Hands of an Angry God , "The God that holds you over the pit of hell, much as one holds a spider, or some loathsome insect over the fire, abhors you, and is dreadfully provoked." Reverend Edwards was comparing God and man to someone holding a spider over a fire. Another excellent illustration of this vivid description is from the same speech, "O sinner! Consider the fearful danger you are in: It is a great furnace of wrath, a wide and bottomless pit, full of the fire of wrath, that you are held over in the hand of that God." This shows that Reverend Edwards also used these figures of speech to strike fear in his audience. He used this fear factor to make the "natural men" of his audience, truly understand the horror of their sins. This style of writing differed so

Hirschi Social Control Theory Essay

I agree with Hirchi’s Theory to a certain extent only. This is because I believe it is not applicable to all people and to all situations. Yes, it may be true that when a person, as early as his childhood, conforms to fit into groups and find his place, he will probably be a person who is responsible and law-abiding. While we still have our own self-interests and individuality, we all want to feel we belong and mould our beliefs and involvements to form attachments. Also, as stated by Hirchi’s Theory, conformity is formed by four variables which we develop through our interactions with family and school, the four being: attachment, commitment, involvement and belief. For me, attachment and conformity to different social groups in the society does not guarantee a person for him to be less ready in committing a crime. Yes, a human being’s personality is partly formed by the environment where he is in—may be the attachment and conformity with his environment helps in molding a righteous and morally-upright personality. But in humanism, a human being has the absolute control to his life. He has free will and it is up to him how he will react to the stimuli created by his environment. In addition, psychologically, the formation of personality is still debatable whether it is nature or nurture. Nature says that a human being’s personality is genetic and on the other hand, nurture says that personality is molded by his environment. I think that some criminals can still be counseled psychologically targeting areas where in he has not yet matured and where he is still fixated—some of these may be the lack of attachment to social groups.

Employment and Unemployment in the 1930s

The Great Depression is to economics what the Big Bang is to physics. As an event, the Depression is largely synonymous with the birth of modern macroeconomics, and it continues to haunt successive generations of economists. With respect to labor and labor markets, these facts evidently include wage rigidity, persistently high unemployment rates, and long-term joblessness. Traditionally, aggregate time series have provided the econometric grist for distinguishing explanations of the Great Depression.Recent research on labor markets in the 1930s, however, has shifted attention from aggregate to disaggregate time series and towards microeconomic evidence. This shift in focus is motivated by two factors. First, disaggregated data provide many more degrees of freedom than the decade or so of annual observations associated with the depression, and thus may prove helpful in distinguishing macroeconomic explanations. Second, disaggregation has revealed aspects of economic behavior hidden in the time series but which may be essential to their proper interpretation and, in any case, are worthy of study in their own right.Although the substantive findings of recent research are too new to judge their permanent significance, I believe that the shift towards disaggregated analysis is an important contribution. The paper begins by reviewing the conventional statistics of the United States labor market during the Great Depression and the paradigms to explain them. It then turns to recent studies of employment and unemployment using disaggregated data of various types. The paper concludes with discussions of research on other aspects of labor markets in the 1930s and on a promising source of microdata for future work.My analysis is confined to research on the United States; those interested in an international perspective on labor markets might begin with Eichengreen and Hatton's chapter in their edited volume, Interwar Unemployment in International Perspective, and the vario us country studies in that volume. I begin by reviewing two standard series of unemployment rates, Stanley Lebergott's and Michael Darby's, and an index of real hourly earnings in manufacturing compiled by the Bureau of Labor Statistics (BLS).The difference between Lebergott's and Darby's series, which is examined later in the paper, concerns the treatment of persons with so-called â€Å"work relief† jobs. For Lebergott, persons on work relief are unemployed, while Darby counts them as employed. Between 1929 and 1933 the unemployment rate increased by over 20 percentage points, according to the Lebergott series, or by 17 percentage points, according to Darby's series. For the remainder of the decade, the unemployment rate stayed in, or hovered around, double digits. On the eve of America's entry into World War Two, between 9. and 14. 6 percent of the labor force was out of work, depending on how unemployment is measured. In addition to high levels of unemployment, the 1930s w itnessed the emergence of widespread and persistent long-term unemployment (unemployment durations longer than one year) as a serious policy problem. According to a Massachusetts state census taken in 1934, fully 63 percent of unemployed persons had been unemployed for a year or more. Similar amounts of long-term unemployment were observed in Philadelphia in 1936 and 1937.Given these patterns of unemployment, the behavior of real wages has proven most puzzling. Between 1929 and 1940 annual changes in real wages and unemployment were positively correlated. Real wages rose by 16 percent between 1929 and 1932, while the unemployment rate ballooned from 3 to 23 percent. Real wages remained high throughout the rest of the decade, although unemployment never dipped below 9 percent, no matter how it is measured. From this information, the central questions appear to be: Why did unemployment remain persistently high throughout the decade?How can unemployment rates in excess of 10 to 20 perc ent be reconciled with the behavior of real wages, which were stable or increasing? One way of answering these questions is to devise aggregative models consistent with the time series, and I briefly review these attempts later in the paper. Before doing so, however, it is important to stress that the aggregate statistics are far from perfect. No government agency in the 1930s routinely collected labor force information analogous to that provided by today's Current Population Survey.The unemployment rates just discussed are constructs, the differences between intercensal estimates of labor force participation rates and employment-to-population ratios. Because unemployment is measured as a residual, relatively small changes in the labor force or employment counts can markedly affect the estimated unemployment rate. The dispute between Darby and his critics over the labor force classification of persons on work relief is a manifestation of this problem. Although some progress has been made on measurement issues, there is little doubt that further refinements to the aggregate unemployment eries would be beneficial. Stanley Lebergott has critically examined the reliability of BLS wage series from the 1930s. The BLS series drew upon a fixed group of manufacturing establishments reporting for at least two successive months. Lebergott notes several biases arising from this sampling method. Workers who were laid off, he claims, were less productive and had lower wages than average. Firms that went out of business were smaller, on average, than firms that survived, and tended to have lower average wages.In addition, the BLS oversampled large firms, and Lebergott suspects that large firms were more adept at selectively laying off lower- productivity labor; more willing to deskill, that is, reassign able employees to less-skilled jobs; and more likely to give able employees longer work periods. A rough calculation suggests that accounting for these biases would produce a n aggregate decline in nominal wages between 1929 and 1932 as much as 48 percent larger than that measured by the BLS series.Although the details of Lebergott's calculation are open to scrutiny, the research discussed elsewhere in the paper suggests that he is correct about the existence of biases in the BLS wage series. For much of the period since World War Two, most economists blamed persistent unemployment on wage rigidity. The demand for labor was a downward sloping function of the real wage but since nominal wages were insufficiently flexible downward, the labor market in the 1930s was persistently in disequilibrium.Labor supply exceeded labor demand, with mass unemployment the unfortunate consequence. Had wages been more flexible, this viewpoint holds, employment would have been restored and Depression averted. The frontal attack on the conventional wisdom was Robert E. Lucas and Leonard Rapping. The original Lucas-Rapping set-up continued to view current labor demand as a ne gative function of the current real wage. Current labor supply was a positive function of the real wage and the expected real interest rate, but a negative function of the expected future wage.If workers expect higher real wages in the future or a lower real interest rate, current labor supply would be depressed, employment would fall, unemployment rise, and real wages increase. Lucas and Rapping offer an unemployment equation, relating the unemployment rate to actual versus anticipated nominal wages, and actual versus anticipated price levels. Al Rees argued that the Lucas-Rapping model was unable to account for the persistence of high unemployment coincident with stable or rising real wages. Lucas and Rapping conceded defeat for the period 1933 to 1941, but claimed victory for 1929 to 1933.As Ben Bernanke pointed out, however, their victory rests largely on the belief that expected real interest rates fell between 1929 and 1933, while â€Å"ex post, real interest rates in 1930-33 were the highest of the century†. Because nominal interest rates fell sharply between 1929 and 1933, whether expected real rates fell hinges on whether deflation — which turned out to be considerable — was unanticipated. Recent research by Steven Cecchetti suggests that the deflation was, at least in part, anticipated, which appears to undercut Lucas and Rapping's reply.In a controversial paper aimed at rehabilitating the Lucas-Rapping model, Michael Darby redefined the unemployment rate to exclude persons who held work relief jobs with the Works Progress and Work Projects Administrations (the WPA) or other federal and state agencies. The convention of the era, followed by Lebergott, was to count persons on work relief as unemployed. According to Darby, however, persons with work relief jobs were â€Å"employed† by the government: â€Å"From the Keynesian viewpoint, labor voluntarily employed on contracyclical †¦ government projects should certainly be counted as employed.On the search approach to unemployment, a person who accepts a job and withdraws voluntarily from the activity of search is clearly employed. † The exclusion of persons on work relief drastically lowers the aggregate unemployment rate after 1935. In addition to modifying the definition of unemployment, Darby also redefined the real wage to be the average annual earnings of full-time employees in all industries. With these changes, the fit of the Lucas-Rapping unemployment equation is improved, even for 1934 to 1941. However, Jonathan Kesselman and N. E.Savin later showed that the improved fit was largely the consequence of Darby's modified real wage series, not the revised unemployment rate. Thus, for the purpose of empirically testing the Lucas-Rapping model, the classification of WPA workers as employed or unemployed is not crucial. Returning to the questions posed above, New Deal legislation has frequently been blamed for the persistence of high unem ployment and the perverse behavior of real wages. In this regard, perhaps the most important piece of legislation was the National Industrial Recovery Act (NIRA) of 1933.The National Recovery Administration (NRA), created by the NIRA, established guidelines that raised nominal wages and prices, and encouraged higher levels of employment through reductions in the length of the workweek (worksharing). An influential study by Michael Weinstein econometrically analyzed the impact of the NIRA on wages. Using aggregate monthly data on hourly earnings in manufacturing, Weinstein showed that the NIRA raised nominal wages directly through its wage codes and indirectly by raising prices.The total impact was such that â€Å"[i]n the absence of the NIRA, average hourly earnings in manufacturing would have been less than thirty-five cents by May 1935 instead of its actual level of almost sixty cents (assuming unemployment to have been unaltered)†. It is questionable, however, whether the NIRA really this large an impact on wages. Weinstein measured the direct effect of the codes by comparing monthly wage changes during the NIRA period (1933-35) with wage changes during the recovery phase (1921-23) of the post-World War One recession (1920-21), holding constant the level of unemployment and changes in wholesale prices.Data from the intervening years (1924-1932) or after the NIRA period were excluded from his regression analysis (p. 52). In addition, Weinstein's regression specification precludes the possibility that reductions in weekly hours (worksharing), some of which occurred independently of the NIRA, had a positive effect on hourly earnings. A recent paper using data from the full sample period and allowing for the effect of worksharing found a positive but much smaller impact of the NIRA on wages (see the discussion of Bernanke's work later in the paper).Various developments in neo-Keynesian macroeconomics have recently filtered into the discussion. Martin Bai ly emphasizes the role of implicit contracts in the context of various legal and institutional changes during the 1930s. Firms did not aggressively cut wages when unemployment was high early in the 1930s because such a policy would hurt worker morale and the firm's reputation, incentives that were later reinforced by New Deal legislation. Efficiency wages have been invoked in a provocative article by Richard Jensen.Beginning sometime after the turn of the century large firms slowly began to adopt bureaucratic methods of labor relations. Policies were â€Å"designed to identify and keep the more efficient workers, and to encourage other workers to emulate them. † Efficiency wages were one such device, which presumably contributed to stickiness in wages. The trend towards bureaucratic methods accelerated in the 1930s. According to Jensen, firms surviving the initial downturn used the opportunity to lay off their least productive workers but a portion of the initial decline in e mployment occurred among firms that went out of business.Thus, when expansion occurred, firms had their pick of workers who had been laid off. Personnel departments used past wage histories as a signal, and higher-wage workers were a better risk. Those with few occupational skills, the elderly (who were expensive to retrain) and the poorly educated faced enormous difficulties in finding work. After 1935 the â€Å"reserve army† of long-term unemployed did not exert much downward pressure on nominal wages because employers simply did not view the long-term unemployed as substitutes for the employed at virtually any wage.A novel feature of Jensen's argument is its integration of microeconomic evidence on the characteristics of the unemployed with macroeconomic evidence on wage rigidity. Other circumstantial evidence is in its favor, too. Productivity growth was surprisingly strong after 1932, despite severe weakness in capital investment and a slowdown in innovative activity. Th e rhetoric of the era, that â€Å"higher wages and better treatment of labor would improve labor productivity†, may be the correct explanation.If the reserve army hypothesis were true, the wages of unskilled workers, who were disproportionately unemployed, should have fallen relative to the wages of skilled and educated workers, but there is no indication that wage differentials were wider overall in the 1930s than in the 1920s. It remains an open question, however, whether the use of efficiency wages was as widespread as Jensen alleges, and whether efficiency wages can account empirically for the evolution of productivity growth in the 1930s. In brief, the macro studies have not settled the debate over the proper interpretation of the aggregate statistics.This state of affairs has much to do with the (supreme) difficulty of building a consensus macro model of the depression economy. But it is also a consequence of the level of aggregation at which empirical work has been con ducted. The problem is partly one of sample size, and partly a reflection of the inadequacies of discussing these issues using the paradigm of a representative agent. This being, the case I turn next to disaggregated studies of employment and unemployment. In a conventional short-run aggregate production function, the labor input is defined to be total person-hours.For the postwar period, temporal variation in person-hours is overwhelmingly due to fluctuations in employment. However, for the interwar period, variations in the length of the workweek account for nearly half of the monthly variance in the labor input. Declines in weekly hours were deep, prolonged, and widespread in the 1930s. The behavior of real hourly earnings, however, may have not have been independent of changes in weekly hours. This insight motivates Ben Bernanke's analysis of employment, hours, and earnings in eight pre-World War Two manufacturing industries.The (industry- specific) supply of labor is described by an earnings function, which gives the minimum weekly earnings required for a worker to supply a given number of hours per week. In Bernanke's formulation, the earnings function is convex in hours and also discontinuous at zero hours (the discontinuity reflects fixed costs of working or switching industries). Production depends separately on the number of workers and weekly hours, and on nonlabor inputs. Firms are not indifferent â€Å"between receiving one hour of work from eight different workers and receiving eight hours from one worker. A reduction in product demand causes the firm to cut back employment and hours per week. The reduction in hours means more leisure for workers, but less pay per week. Eventually, as weekly hours are reduced beyond a certain point, hourly earnings rise. Further reductions in hours cannot be matched one for one by reductions in weekly earnings. But, when hourly earnings increase, the real wage then appears to be countercyclical. To test the mode l, Bernanke uses monthly, industry-level data compiled by the National Industrial Conference Board covering the period 1923 to 1939.The specification of the earnings function (describing the supply of labor) incorporates a partial adjustment of wages to prices, while the labor demand equation incorporates partial adjustment of current demand to desired demand. Except in one industry (leather), the industry demand for workers falls as real product wages rise; industry demands for weekly hours fall as the marginal cost to the firm of varying weekly hours rises; and industry labor supply is a positive function of weekly earnings and weekly hours.The model is used to argue that the NIRA lowered weekly hours and raised weekly earnings and employment, although the effects were modest. In six of the industries (the exceptions were shoes and lumber), increased union influence after 1935 (measured with a proxy variable of days idled by strikes) raised weekly earnings by 10 percent or more. S imulations revealed that allowing for full adjustment of nominal wages to prices resulted in a poor description of the behavior of real wages, but no deterioration in the model's ability to explain employment and hours variation.Whatever the importance of sticky nominal wages in explaining real wage behavior, the phenomenon â€Å"may not have had great allocative significance† for employment. In a related paper, Bernanke and Martin Parkinson use an expanded version of the NICB data set to explore the possibility that â€Å"short-run increasing returns to labor† or procyclical labor productivity, characterized co-movements in output and employment in the 1930s. Using their expanded data set, Bernanke and Parkinson estimate regressions of the change in output on the change in labor input, now defined to be total person-hours.The coefficient of the change in the labor input is the key parameter; if it exceeds unity, then short-run increasing returns to labor are present. Bernanke and Parkinson find that short-run increasing returns to labor characterized all but two of the industries under study (petroleum and leather). The estimates of the labor coefficient are essentially unchanged if the sample is restricted to just the 1930s. Further, a high degree of correlation (r = 0. 9) appears between interwar and postwar estimates of short-run increasing returns to labor for a matched sample of industries.Thus, the procyclical nature of labor productivity appears to be an accepted fact for both the interwar and postwar periods. One explanation of procyclical productivity, favored by real business cycle theorists, emphasizes technology shocks. Booms are periods in which technological change is unusually brisk, and labor supply increases to take advantage of the higher wages induced by temporary gains in productivity (caused by the outward shift in production functions).In Bernanke and Parkinson's view, however, the high correlation between the pre- and post -war estimates of short-run increasing returns to labor poses a serious problem for the technological shocks explanation. The high correlation implies that the â€Å"real shocks hitting individual industrial production functions in the interwar period accounted for about the same percentage of employment variation in each industry as genuine technological shocks hitting industrial production functions in the post-war period†.However, technological change per se during the Depression was concentrated in a few industries and was modest overall. Further, while real shocks (for example, bank failures, the New Deal, international political instability) occurred, their effects on employment were felt through shifts in aggregate demand, not through shifts in industry production functions. Other leading explanations of procyclical productivity are true increasing returns or, popular among Keynesians, the theory of labor hoarding during economic downturns.Having ruled out technology s hocks, Bernanke and Parkinson attempt to distinguish between true increasing returns and labor hoarding. They devise two tests, both of which involve restrictions on excluding proxies for labor utilization from their regressions of industry output. If true increasing returns were present, the observed labor input captures all the relevant information about variations in output over the cycle. But if labor hoarding were occurring, the rate of labor utilization, holding employment constant, should account for output variation.Their results are mixed, but are mildly in favor of labor hoarding. Although Bernanke's modeling effort is of independent interest, the substantive value of his and Parkinson's research is enhanced considerably by disaggregation to the industry level. It is obvious from their work that industries in the 1930s did not respond identically to decreases in output demand. However, further disaggregation to the firm level can produce additional insights. Bernanke and P arkinson assume that movements in industry aggregates reflect the behavior of a representative firm.But, according to Lebergott (1989), much of the initial decline in output and employment occurred among firms that exited. Firms that left, and new entrants, however, were not identical to firms that survived. These points are well-illustrated in Timothy Bresnahan and Daniel Raff's study of the American motor vehicle industry. Their database consists of manuscript census returns of motor vehicle plants in 1929, 1931, 1933, and 1935. By linking the manuscript returns from year to year, Bresnahan and Raff have created a panel dataset, capable of identifying plants the exited, surviving plants, and new plants.Plants that exited between 1929 and 1933 had lower wages and lower labor productivity than plants that survived. Between 1933 and 1935 average wages at exiting plants and new plants were slightly higher than at surviving plants. Output per worker was still relatively greater at surv iving plants than new entrants, but the gap was smaller than between 1929 and 1933. Roughly a third of the decline in the industry's employment between 1929 and the trough in 1933 occurred in plant closures. The vast majority of these plant closures were permanent.The shakeout of inefficient firms after 1929 ameliorated the decline in average labor productivity in the industry. Although industry productivity did decline, productivity in 1933 would have been still lower if all plants had continued to operate. During the initial recovery phase (1933-35) about 40 percent of the increase in employment occurred in new plants. Surviving plants were more likely to use mass-production techniques; the same was true of new entrants. Mass production plants differed sharply from their predecessors (custom production plants) in the skill mix of their workforces and in labor relations.In the motor vehicle industry, the early years of the Depression were an â€Å"evolutionary event†, perman ently altering the technology of the representative firm. While the representative firm paradigm apparently fails for motor vehicles, it may not for other industries. Some preliminary work by Amy Bertin, Bresnahan, and Raff, on another industry, blast furnaces, is revealing on this point. Blast furnaces were subject to increasing returns and the market for the product (molten iron) was highly localized.For this industry, reductions in output during a cyclical trough are reasonably described by a representative firm, since â€Å"localized competition prevented efficient reallocation of output across plants† and therefore the compositional effects occurring in the auto industry did not happen. These analyses of firm-level data have two important implications for studies of employment in the 1930s. First, aggregate demand shocks could very well have changed average technological practice through the process of exit and entry at the firm level.Thus Bernanke and Parkinson's reject ion of the technological shocks explanation of short-run increasing returns, which is based in part on their belief that aggregate demand shocks did not alter industry production functions, may be premature. Second, the empirical adequacy of the representative firm paradigm is apparently industry-specific, depending on industry structure, the nature of product demand, and initial (that is, pre-Depression) heterogeneity in firm sizes and costs.Such â€Å"phenomena are invisible in industry data,† and can only be recovered from firm-level records, such as the census manuscripts. Analyses of industry and firm-level data are one way to explore heterogeneity in labor utilization. Geography is another. A focus on national or even industry aggregates obscures the substantial spatial variation in bust and recovery that characterized the 1930s. Two recent studies show how spatial variation suggests new puzzles about the persistence of the Depression as well as provide additional degre es of freedom for discriminating between macroeconomic models.State-level variation in employment is the subject of an important article by John Wallis. Using data collected by the Bureau of Labor Statistics, Wallis has constructed annual indices of manufacturing and nonmanufacturing employment for states from 1930 to 1940. Wallis' indices reveal that declines in employment between 1930 and 1933 were steepest in the East North Central and Mountain states; employment actually rose in the South Atlantic states, however, once an adjustment is made for industry mix.The South also did comparatively well during the recovery phase of the Depression (1933-1940). Wallis tests whether the southern advantage during the recovery phase might reflect lower levels of unionization and a lower proportion of employment affected by the passage of the Social Security Act (1935), but controlling for percent unionized and percent in covered employment in a regression of employment growth does not elimina te the regional gap. What comes through clearly,† according to Wallis â€Å"is that the [employment] effects of the Depression varied considerably throughout the nation† and that a convincing explanation of the South-nonSouth difference remains an open question. Curtis Simon and Clark Nardinelli exploit variation across cities to put forth a particular interpretation of economic downturn in the early 1930s. Specifically, they study the empirical relationship between â€Å"industrial diversity† and city- level unemployment rates before and after World War Two.Industrial diversity is measured by a city-specific Herfindahl index of industry employment shares. The higher the value of the index, the greater is the concentration of employment in a small number of industries. Using data from the 1930 federal census and the 1931 Special Census of Unemployment, Simon and Nardinelli show that unemployment rates and the industrial diversity index were positively correlated across cities at the beginning of the Depression.Analysis of similar census data for the post-World War Two, period, reveals a negative correlation between city unemployment rates and industrial diversity. Simon and Nardinelli explain this finding as the outcome of two competing effects. In normal economic circumstances, a city with a more diverse range of industries should have a lower unemployment rate (the â€Å"portfolio† effect), because industry-specific demand shocks will not be perfectly correlated across industries and some laid-off workers will find ready employment in expanding industries.The portfolio effect may fail, however, during a large aggregate demand shock (the early 1930s) if firms and workers are poorly informed, misperceiving the shock to be industry-specific, rather than a general reduction in demand. Firms in industrially diverse cities announce selective layoffs rather than reduce wages, because they believe that across-the-board wage cuts would caus e too many workers to quit (workers in industrial diverse cities think they can easily find a job in another industry elsewhere in the same city), thus hurting production.Firms in industrially specialized cities, however, are more likely to cut wages than employment because they believe lower wages â€Å"would induce relatively fewer quits† than in industrially diverse cities. Thus, Simon and Nardinelli conclude, wages in the early 1930s were more rigid in industrially-diverse cities, producing the positive correlation between industrial diversity and unemployment. Improvements in the quantity, quality, and timeliness of economic information, they conjecture, have caused the portfolio effect to dominate after World War Two, producing the postwar negative correlation.Although one can question the historical relevance of Simon and Nardinelli's model, and the specifics of their empirical analysis, their paper is successful in demonstrating the potential value of spatial data in unraveling the sources of economic downturn early in the Depression. Postwar macroeconomics has tended to proceed as aggregate unemployment rates applied to a representative worker, with a certain percentage of that worker's time not being used. As a result, disaggregated evidence on unemployment has been slighted.Such evidence, however, can provide a richer picture of who was unemployed in the 1930s, a better understanding of the relationship between unemployment and work relief, and further insights into macroeconomic explanations of unemployment. To date, the source that has received the most attention is the public use tape of the 1940 census, a large, random sample of the population in 1940. The 1940 census is a remarkable historical document. It was the first American census to inquire about educational attainment, wage and salary income and weeks worked in the previous year; nd the first to use the â€Å"labor force week† concept in soliciting information about labor f orce status. Eight labor force categories are reported, including whether persons held work relief jobs during the census week (March 24-30, 1940). For persons who were unemployed or who held a work relief job at the time of the census, the number of weeks of unemployment since the person last held a private or nonemergency government job of one month or longer was recorded.The questions on weeks worked and earnings in 1939 did not treat work relief jobs differently from other jobs. That is, earnings from, and time spent on, work relief are included in the totals. I have used the 1940 census sample to study the characteristics of unemployed workers and of persons on work relief, and the relationship between work relief and various aspects of unemployment. It is clear from the census tape that unemployed persons who were not on work relief were far from a random sample of the labor force.For example, the unemployed were typically younger, or older, than the average employed worker (u nemployment followed a U-shape pattern with respect to age); the unemployed were more often nonwhite; and they were less educated and had fewer skills than employed persons, as measured by occupation. Such differences tended to be starkest for the long-term unemployed (those with unemployment durations longer than year); thus, for example, the long-term unemployed had even less schooling that the average unemployed worker.Although the WPA drew its workers from the ranks of the unemployed, the characteristics of WPA workers did not merely replicate those of other unemployed persons. For example, single men, the foreign-born, high school graduates, urban residents, and persons living in the Northeast were underrepresented among WPA workers, compared with the rest of the unemployed. Perhaps the most salient difference, however, concerns the duration of unemployment. Among those on work relief in 1940, roughly twice as many had been without a non-relief job for a year or longer as had u nemployed persons not on work relief.The fact that the long-term unemployed were concentrated disproportionately on work relief raises an obvious question. Did the long-term unemployed find work relief jobs after being unemployed for a long time, or did they remain with the WPA for a long time? The answer appears to be mostly the latter. Among nonfarm males ages 14 to 64 on work relief in March 1940 and reporting 65 weeks of unemployment (that is, the first quarter of 1940 and all of 1939), close to half worked 39 weeks or more in 1939. Given the census conventions, they had to have been working more or less full time, for the WPA.For reasons that are not fully clear, the incentives were such that a significant fraction of persons who got on work relief, stayed on. One possible explanation is that some persons on work relief preferred the WPA, given prevailing wages, perhaps because their relief jobs were more stable than the non-relief jobs (if any) available to them. Or, as one WP A worker put it: â€Å"Why do we want to hold onto these [relief] jobs? †¦ [W]e know all the time about persons †¦ just managing to scrape along †¦ My advice, Buddy, is better not take too much of a chance. Know a good thing when you got it. Alternatively, working for the WPA may have stigmatized individuals, making them less desirable to non-relief employers the longer they stayed on work relief. Whatever the explanation, the continuous nature of WPA employment makes it difficult to believe that the WPA did not reduce, in the aggregate, the amount of job search by the unemployed in the late 1930s. In addition to the duration of unemployment experienced by individuals, the availability of work relief may have dampened the increase in labor supply of secondary workers in households in which the household head was unemployed, the so- called â€Å"added worker† effect.Specifically, wives of unemployed men not on work relief were much more likely to participate in the labor force than wives of men who were employed at non-relief jobs. But wives of men who worked for the WPA were far less likely to participate in the labor force than wives of otherwise employed men. The relative impacts were such that, in the aggregate, no added worker effect can be observed as long as persons on work relief are counted among the unemployed.Although my primary goal in analyzing the 1940 census sample was to illuminate features of unemployment obscured by the aggregate time series, the results bear on several macroeconomic issues. First, the heterogenous nature of unemployment implies that a representative agent view of aggregate unemployment cannot be maintained for the late 1930s. Whether the view can be maintained for the earlier part of the Depression is not certain, but the evidence presented in Jensen and myself suggests that it cannot.Because the evolution of the characteristics of the unemployed over the 1930s bears on the plausibility of various macro economic explanations of unemployment (Jensen's use of efficiency wage theory, for example), further research is clearly desirable. Second, the heterogenous nature of unemployment is consistent with Lebergott's claim that aggregate BLS wage series for the 1930s are contaminated by selection bias, because the characteristics that affected the likelihood of being employed (for example, education) also affected a person's wage.Again, a clearer understanding of the magnitude and direction of bias requires further work on how the characteristics of the employed and unemployed changed as the Depression progressed. Third, macroeconomic analyses of the persistence of high unemployment should not ignore the effects of the WPA — and, more generally, those of other federal relief policies — on the economic behavior of the unemployed. In particular, if work relief was preferred to job search by some unemployed workers, the WPA may have displaced some growth in private sector emplo yment that would have occurred in its absence.An estimate of the size of this displacement effect can be inferred from a recent paper by John Wallis and Daniel Benjamin. Wallis and Benjamin estimate a model of labor supply, labor demand, and per capita relief budgets using panel data for states from 1933 to 1939. Their coefficients imply that elimination of the WPA starting in 1937 would have increased private sector employment by 2. 9 percent by 1940, which corresponds to about 49 percent of persons on work relief in that year. Displacement was not one-for-one, but may not have been negligible.My discussion thus far has emphasized the value of disaggregated evidence in understanding certain key features of labor markets in the 1930s — the behavior of wages, employment and unemployment — because these are of greatest general interest to economists today. I would be remiss, however, if I did not mention other aspects of labor markets examined in recent work. What follow s is a brief, personal selection from a much larger literature. The Great Depression left its mark on racial and gender differences.From 1890 to 1930 the incomes of black men increased slightly relative to the incomes of white men, but the trend in relative incomes reversed direction in the 1930s. Migration to the North, a major avenue of economic advancement for Southern blacks, slowed appreciably. There is little doubt that, if the Depression had not happened, the relative economic status of blacks would have been higher on the eve of World War Two. Labor force participation by married women was hampered by â€Å"marriage bars†, implicit or explicit regulations which allowed firms to dismiss single women upon arriage or which prohibited the hiring of married women. Although marriage bars existed before the 1930s, their use spread during the Depression, possibly because social norms dictated that married men were more deserving of scarce jobs than married women. Although the y have not received as much attention from economists, some of the more interesting effects of the Depression were demographic or life-cycle in nature. Marriage rates fell sharply in the early 1930s, and fertility rates remained low throughout the decade.An influential study by the sociologist Glen Elder, Jr. traced the subsequent work and life histories of a sample of individuals growing up in Oakland, California in the 1930s. Children from working class households whose parents suffered from prolonged unemployment during the Depression had lower educational attainment and less occupational mobility than their peers who were not so deprived. Similar findings were reported by Stephan Thernstrom in his study of occupational mobility of Boston men.The Great Depression was the premier macroeconomic event of the twentieth century, and I am not suggesting we abandon macroeconomic analysis of it. I am suggesting, however, that an exclusive focus on aggregate labor statistics runs two risk s: the facts derived may be artifacts, and much of what may be interesting about labor market behavior in the 1930s is rendered invisible. The people and firms whose experiences make up the aggregates deserve to be studied in their diversity, not as representative agents.I have mentioned census microdata, such as the public use sample of the 1940 census or the manufacturing census manuscripts collected by Bresnahan and Raff, in this survey. In closing, I would like highlight another source that could be examined in future work. The source is the â€Å"Study of Consumer Purchases in the United States† conducted by the BLS in 1935-36. Approximately 300,000 households, chosen from a larger random sample of 700,000, supplied basic survey data on income and housing, with 20 percent furnishing additional information.The detail is staggering: labor supply and income of all family members, from all sources (on a quarterly basis); personal characteristics (for example, occupation, age , race); family composition; housing characteristics; and a long list of durable and non-durable consumption expenditures (the 20 percent sample). Because the purpose of the study was to provide budget weights to update the CPI, only families in â€Å"normal† economic circumstances were included (this is the basis for the reduction in sample size from 700,000 to 300,000).Thus, for example, persons whose wages were very low or who experienced persistent unemployment are unlikely to be included in 1935-36 study. A pilot sample, drawn from the original survey forms (stored at the National Archives) and containing the responses of 6,000 urban households, is available in machine-readable format from the Inter-University Consortium for Political and Social Research at the University of Michigan (ICPSR Study 8908). Robert A. Margo Vanderbilt University