Men of Athens Who Contributed to the Rise of Democracy

Way back when there wasnt a draft and people didnt look to the military for a paycheck, although they may have seen it as an avenue to great wealth. Ancient cultures, including Athens, expected their wealthier citizens to serve as soldiers, providing their own horses, chariots, weapons and armors, and reaping rewards, if they won, through pillaging. When ancient Athens needed more bodies for their military, they looked to ordinary citizen soldiers to augment the aristocracys cavalry. These soldiers were small farmers barely able to stave off starvation for themselves and their families. Being required to serve in the military might provide plunder, but it would provide a hardship because the able bodies would be absent when they were most needed for agriculture. Early Armies Manned By the Wealthy As long as the military strength of a country depends on cavalry, the nobles and those with sufficient wealth to provide horses have a legitimate claim to power. After all, its their lives and goods on the line. This was the case in Ancient Athens. And indeed the earliest form of constitution among the Greeks after the kingships consisted of those who were actually soldiers, the original form consisting of the cavalry for war had its strength and its pre-eminence in cavalry, since without orderly formation heavy-armed infantry is useless, and the sciences and systems dealing with tactics did not exist among the men of old times, so that their strength lay in their cavalry; but as the states grew and the wearers of heavy armor had become stronger, more persons came to have a part in the government.Aristotle Politics 1297B Need More Soldiers? Decrease the Qualifications But with the rise of the hoplite, non-equestrian army, ordinary citizens of Athens could become valued members of society. For Athens, the hoplite warrior was not the poorest of the poor. Each hoplite had to have enough wealth to provide himself the requisite body armor to fight in the phalanx. Know that this is good for the city and for the whole people, when a man takes his place in the front line of fighters and keeps his position unflinchingly, has no thought at all of shameful flight, gives himself an enduring heart and soul, stands by his neighbour and speak words of encouragement to him: this is a good man in war.Tyrtaeus Fr. 12 15-20 Rich vs Poor in Athens By becoming a part of the hoplite phalanx, an ordinary citizen of Athens was demonstrably important. Along with his military importance came a sense that he had a right to be involved in decision-making processes. [See Four Tribes and the Ancient Social Order in Athens.] War meant the small farmer / ordinary citizen had to leave his farm, which could fail and his family starve unless a conclusion to the battle in which he was fighting was reached by the time he was needed to work his field. [See Land Shortage in Athens.] In addition, some of the aristocracy (known as eupatrids) became wealthier than ever because an economy based on the exchange of commodities was replaced by coinage. The first clear sign of a new tension caused by the economy that developed between the eupatrids and the ordinary citizens was Cylons attempt to usurp power in Athens. Olympic Athlete Cylon, an Athenian nobleman or  eupatrid, was an Olympic athlete whose victory in 640 B.C. won him a kings daughter and access  to  the top position in Athens. He married the daughter of Theagenes, the  tyrant  of Megara [see  map section I e-f].  A  tyrant, in the 7th century B.C., meant something different from our modern concept of a tyrant  as a cruel and oppressive despot. A tyrant was a usurper in ancient Greece. Think coup detat. He was  a leader who had overturned an existing regime and took control of the government. Tyrants even had some measure of popular support, usually. [The concept is complicated. For a detailed look, see  Ancient Tyranny, by Sian Lewis.] Botched Coup Cylon wished to become tyrant of Athens. It is possible he had radical reforming tendencies that would have appealed to poor farmers. Even if he did not, he must have counted on their support, but it never came. Backed mainly by his father-in-law Theagenes threatening forces, Cylon attacked the Acropolis in Athens. Cylon thought he had selected an auspicious day, but his interpretation of the  Delphic Oracle  had been wrong (according to Thucydides). The Oracle had told him that he could become tyrant during the great festival of Zeus. Zeus was honored on more than one annual occasion and Cylon had made assumptions without adequate information. Cylon assumed it was the Olympic festival. Curse of the  Alcmaeonids Cylon lacked a broad base of support, perhaps because the Athenians feared he would be a puppet of his father-in-law. At any rate, his plot failed. To save their lives, some of his fellow conspirators sought sanctuary in the Temple of Athena Polias. Unfortunately for them, in 632 B.C., Megacles of the Alcmaeonids was archon. He ordered the killing of Cylons supporters. Although his supporters were killed, Cylon and his brother managed to escape. Neither they nor their descendants were ever to return to Athens. The People Get Fed Up The privileged  eupatrid  (aristocratic) few in Athens had been making all the decisions for long enough. By 621 B.C. the rest of the people of Athens were no longer willing to accept arbitrary, oral rules of the  eupatrid  thesmothetai  those who lay down the law and judges. Draco was appointed to write down the laws. Athens may have been a late-comer to the written law code since it may already have been done elsewhere in the Hellenic world. Problems Introduced by the Law Code of Draco Whether or not it was intentional, when Draco codified the laws, it brought to public attention Athens outrageous and archaic penalties. Part of the excess was Draco himself. The story goes that when asked about the harshness of his punishments, Draco said the death penalty was appropriate for stealing  even so much as a cabbage. If there had been a worse penalty than death, Draco would gladly have applied it to greater crimes. As a result of Dracos strict, unforgiving code, the adjective based on the name Draco -- draconian -- refers to penalties considered excessively severe. And Draco himself, they say, being asked why he made death the penalty for most offences, replied that in his opinion the lesser ones deserved it, and for the greater ones no heavier penalty could be found.Plutarch Life of Solon Slavery For Debt Through the laws of Draco, those in debt could be made slaves -- but only if they were members of the lower class. This means members of a  genos  (the  gennetai) could not be sold as slaves, yet their hangers-on (orgeones) could. Homicide Another result of the codification of laws by Draco -- and the only part that remained part of the legal code -- was the introduction of the concept of intention to murder. Murder could be manslaughter (either justifiable or accidental) or intentional homicide. With the new law code, Athens, as a city-state, would intervene in what were formerly family matters of blood-feuds. Greek Terms AlcmaeonidsThe Alcmaeonids were a powerful family of Athens descended from Alcmaeon, son of Nestor. Megacles, son of Alcmaeon, was the archon responsible for killing the followers of Cylon. Cleisthenes, son of Megacles, was archon in 525. Pericles and Alcibiades were other noteworthy Alcmaeonids. ArchonThe word archon is applied to certain officials who were in the time  appointed by lot and held office for a limited period of time in ancient Athens. One of these archons is referred to as the eponymous archon because the period of his archonship was referred to by his name. This is important for dating events in  Greek history.More on Archons AthensAthens is named  after  its  patron goddess Athena.  On top of its highpoint, known as the acropolis,  were  Athens important temples, especially, the Parthenon. Since the acropolis was easily made defensible with walls, cities, including Athens, formed around them, citizens gathering within in times of attack. Northwest o f the acropolis was the Areopagus where homicide cases were tried. The assembly met on the  Pnyx hill. The center of Athens was the agora, an open public  place, and market. EupatridsThe well-born or aristocracy of Athens. The /eu/ means good or well and the patrid refers to the father as in  patriarchy, so the well-born are well-fathered. HopliteThe Hoplites were the heavily armed infantry soldiers of the Greeks. It is thought by many that the name hoplite comes from a Greek word hoplon for a specific shape (large and round) of the shield  with a flat offset rim (itus) and two handles on the inside possibly invented by 700 B.C.More on Hoplites PolisIn the ancient world, from before the time of empires and modern-style countries or nations, political entities were cities and the environs. These cities constituted the states, making them city-states. The Greek form was the polis. ThesmothetaiThe 6 archons of Athens known as the  thesmothetai  were the layers down of the l aw.

Interviewing a Manager Essay - 1577 Words

Introduction When we were given the task of interviewing a manager; many questions and thoughts came to mind. But the main thing we were worried about was â€Å"Whom would we interview?†We were lucky enough to have a close connection within the group to Mr John Doe; the National Retail Field Operations Manager of Nova Energy. We set out to interview him with the aim of gaining some insight on what being a manager truly involves on a business and personal level and how we could become strong managers in the future. Background We chose to interview Mr. John Doe, the National Retail Field Operations Manager of Nova Energy, for multiple reasons, one being that he works from home which gave us an interesting angle for our report, because at†¦show more content†¦It has also recently invested in a tidal electricity generation project (Nova Energy, 2014). Russells position within the business is one of the top tiers of management within the company, he is a part of a team of five other managers and then he himself manages another management team of six, that run the Retail and Operations sector of Nova Energy. Findings Great responsibilities come with the role of National Retail Fields Operations Manager, it requires skills such as communication and leadership to move through day to day tasks. Russells particular position requires him to assist and coordinate the product flow in the field or as he described â€Å"supply the product to the punters† (Walsh, 2014). Therefore he is responsible for all that falls outside the administrative office and comes under his sector of retail and operations in the energy division, including organising thousands of gas meter readings, operations of solar factories, hired contractors, million dollar expansion projects etc. He is a part of a 5 person management team in charge of Nova energy as a whole, who are expected to hold meetings weekly to allocate tasks, update and discuss progress/issues within their individual sectors. Six other employees fall directly under Doe whom he calls his â€Å"direct reports† (Walsh, 2014), these are the people who he delegate’s areas needing their attention andShow MoreRelatedInterviewing A Human Resource Manager Essay801 Words   |  4 PagesInterviewing a Human Resource Manager I chose to interview Randy Bedsaul. He is an older gentleman who responds in a genuine manner. 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Information Security Privacy and Security Issues

Question: Discuss about the Information Security for Privacy and Security Issues. Answer: Introduction The Big data is one of the emerging areas that are used to manage datasets, whose size is beyond the capability of commonly used software tools for capturing, managing and analyzing the amount of data. According to Sagiroglu and Sinanc ( 2013), conventional security systems are tailored to computer infrastructures which are confined with well defined perimeter of security as the public clouds helps big data in expanding. The report endorses the significant aspects that are related with the security and privacy of big data. The contents of the report helps in unearthing the challenges that are related with big data, relevant technologies associated with big data, its applications and their impacts. Description about the Privacy and security issues associated with Big Data According to Kaisler et al. ( 2013), with the increase in accessibility of big data, privacy as well as security concerns are growing day by day. Data sharing has become one of the most significant tasks before the governmental agencies, scientist and businessman. The technologies as well as tools are developed for managing the data sets which are not designed for proper privacy or security measures. On the other hand, Kim et al. (2014) argued that the tools and technologies are not incorporated adequately for security measures due to lack of training and fundamental understanding about the requirement. The procedure of big data also lacks adequate policies for ensuring compliance with the present approaches of privacy as well as security (Hashem et al., 2015). The present technological advancement towards privacy or security of data is increasingly being breached. It is done either intentionally or it happens accidentally, therefore the most important need is to update the present a pproaches in order to prevent the challenges and issues that are associated with the process of data leaking. Challenges associated with Big Data The Big Data is an area of risk that needs to be considered as it includes lifecycle which is associated with the ownership as well as classification of data on the basis of collection and creation procedure and lack of security processes (Riggins Wamba, 2015). As Big Data is one of the significant as well as complex topic it is always associated with the challenges and security issues. The challenges of Big Data have a direct impact on the designs of security issues that are required for tackling the characteristics and requirements. According to Kshetri (2014), CSA has divided the different challenges of big data which are associated with the privacy as well as security issues in four different aspects of the big data ecosystems. The aspects include security of Infrastructure, Data management, Data security Reactive security and Integrity. Each of the aspects faces lot of security issues which includes secured Distributed Data processing, Granular audits, Data security associated with Cryptographic solutions, Secure storage and Transaction logs associated with data and many more (Chaudhuri, 2015). All this security as well as the challenges that are related with the privacy of Big Data covers the whole spectrum of the cycle of Big Data, Its sources of data production, Storage and processing of data, data transportation and storage on different devices. On the other hand, Tene and Polonetsky (2012) argued that a specific aspect of Big data security and privacy needs to be related with the rise of internet of thin gs. The increase in the number of connected devices has led the manufacturers in the market for short period of time for exploiting the opportunity. It helps in providing tremendous benefit and opportunities to the users who are responsible for security or privacy challenges. According to Inukollu et al. (2014), there are many identified security issues which are associated with the insecure web interface, insufficient authentication and insure services of network. Insecure web interface allows an attacker to exploit the web interface of the administration and thus it helps in unauthorized access to control the internet of things device. Insufficient authorization also raises privacy concerns. It allows a hacker to exploit the policy of password in order to access the privileged mode on the devices of IoT (Marx, 2013). Insecure network services exploits services of the devices that are related with the devices of Internet of Things. On the other hand, Grolinger et al. (2014) stated that few more privacy concerns or challenges that are related with the security system of Big Data. The challenges are due to insecure interface of mobile, insufficient configurability of security and insecure cloud interface. Due to lack of configuration, an attacker can easil y access the data or have control on the devices (Action et al., 2014).It is also stated that without effective security control an hacker or attacker can use various vectors such as account enumeration, insufficient authentication for accessing data with the help of the mobile interface. Description of relevant technologies The topic of big data encompasses many trends which includes development of new technologies that helps the users to consider and handle the Big Data properly. According to Wu et al. (2014), there is no comprehensive Big Data technology for resolving the challenges because the big data project companies are very much different from one another therefore, a proven complete certification is not yet provided although some of the vendors like IBM have announced several programs related with certification. On the other hand, Boyd and Crawford (2012) stated that hadoop is synonymous with the term big data and it is very much famous for handing huge amount of data. The Distributed file system of Hadoop helps in enabling highly scalable as well as redundant storage of data for executing various types of projects. Analytical databases are used for the purpose of data processing. Many of the techniques use connectors in order to integrate with the system of Hadoop (Dou et al., 2015). The techn ology of big data is divided into two components which are software and hardware component. The hardware component of the structure consists of infrastructure layer whereas the software part or the component is categorized into management software, discovery and analytics software, automation and decision support software. According to Kaushik and Jain (2014), Infrastructure is considered to be the foundation of Big Data technology stack. The main components that are very much necessary for the storage procedure includes standard of the industry, servers and networking bandwidth of about 10 Gbps. The storage systems are designed in a very much flexible way for supporting capabilities in memory delivered systems. On the other hand, Wu et al. (2014) stated that the layers that are associated with the processes of the software and prepares both structured as well as unstructured analysis helps in extracting, normalizing and integrating data. The architectures of data management and organization include RDBMS (Relational Database Management System ) and the NoSQL database management system (Action et al., 2014). The database management systems are designed in order to manage different types of data. Application of the technologies According to Grolinger et al. (2014), Apache Hadoop has several applications in lowering the cost barriers that are related with processing and analyzing of big data. Technical barriers remain but the applications that are related with the Hadoop system are highly complex. On the other hand, Boyd and Crawford (2012) stated that there are many application of Hadoop system. It is mainly used in analyzing life-threatening risks, warning signs for security breaches and also helps in preventing hardware failure. According to Marx (2013), machines create a lot of information in order to explore the applications of Hadoop. Capturing data from HVAC systems helps in identifying problems with locations and products. On the other hand, Tene and Polonetsky (2012) argued that hadoop are used in streaming projects, complex event processing, replacing SAS. In order to make the Hadoop applications accessible thoroughly to the organizations, the system needs to be integrated for the overall flow of data. Talend Open Studio is one of the ideal tools that help in integrating the application inside the architecture of data (Chaudhuri, 2015).It helps in providing more built-in connector components than any other integration of data. The connectors help in writing in any format, database or packed enterprise application. Clarification of Vague Areas According to Kaushik and Jain (2014), despite of the presence of Big Data technologies that are available in the market, enterprises are struggling a lot in order to take proper advantage of the big data. It is because the organizations fail to fulfill certain criterias which include implementing mechanism for combining data from different sources and proper industrializing of the entire data (Grolinger et al., 2014). Combining technology stacks for facilitating successful effective aggregation, analysis, ingestion and combining data for providing ROI for the implementation purpose of Big Data. The organizations must have to jump over some of the hurdles for implementing effective and proper strategies that must be related with Big Data. On the other hand, Riggins and Wamba (2015) stated that for resolving the challenges the enterprises needs to follow some steps. It includes codifying problems that are solved with the help of Big Data. The experts of the enterprise must need to agree upon certain criterion which helps in explaining the type of data that is collected and its sources from where the data is collected. The resolving procedure also includes creation of right data that are required for the core implementation by processing the collected data (Tene and Polonetsky, 2012). The enterprises always increase the size of the data sample without taking much time for verifying whether the model is accurate or not. If the data model is tested and the test is successful, then also the enterprises have to be careful. Conclusion It can be concluded that the Big Data faces lot of challenges due to privacy or security issues. There is lot of challenges which needs to solve in order to mitigate the issues. The Big Data is an area of risk that desires to be considered as it includes lifecycle which is related with the possession as well as categorization of data on the basis of gathering and formation procedure and lack of security processes. It is analyzed that there are several gaps in the technologies that are used for managing and processing Big Data analytics. Therefore proper steps and measures needs to be considered in order to reduce the gaps as well as in mitigating the challenges. References Action, C., Watchdog, C., Rights, P. P., Clearinghouse, P. R., American Library Association. (2014). Coalition Letter to Director Holden to Petition for OSTP to Conduct a Public Comment Process on Big Data and the Future of Privacy. Boyd, D., Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon.Information, communication society,15(5), 662-679. Chaudhuri, S. (2012, May). What next?: a half-dozen data management research goals for big data and the cloud. InProceedings of the 31st ACM SIGMOD-SIGACT-SIGAI symposium on Principles of Database Systems(pp. 1-4). ACM. Dou, W., Zhang, X., Liu, J., Chen, J. (2015). HireSome-II: Towards privacy-aware cross-cloud service composition for big data applications.IEEE Transactions on Parallel and Distributed Systems,26(2), 455-466. Grolinger, K., Hayes, M., Higashino, W. A., L'Heureux, A., Allison, D. S., Capretz, M. A. (2014, June). Challenges for mapreduce in big data. In2014 IEEE World Congress on Services(pp. 182-189). IEEE. Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., Khan, S. U. (2015). The rise of big data on cloud computing: Review and open research issues.Information Systems,47, 98-115. Inukollu, V. N., Arsi, S., Ravuri, S. R. (2014). Security issues associated with big data in cloud computing.International Journal of Network Security Its Applications,6(3), 45. Kaisler, S., Armour, F., Espinosa, J. A., Money, W. (2013, January). Big data: issues and challenges moving forward. InSystem Sciences (HICSS), 2013 46th Hawaii International Conference on(pp. 995-1004). IEEE. Kaushik, M., Jain, A. (2014). Challenges to Big Data Security and Privacy.International Journal of Computer Science and Information Technologies (IJCSIT),5(3), 3042-3043. Kim, G. H., Trimi, S., Chung, J. H. (2014). Big-data applications in the government sector.Communications of the ACM,57(3), 78-85. Kshetri, N. (2014). Big dataÃâ€" ³ s impact on privacy, security and consumer welfare.Telecommunications Policy,38(11), 1134-1145. Marx, V. (2013). Biology: The big challenges of big data.Nature,498(7453), 255-260. Riggins, F. J., Wamba, S. F. (2015, January). Research directions on the adoption, usage, and impact of the internet of things through the use of big data analytics. InSystem Sciences (HICSS), 2015 48th Hawaii International Conference on(pp. 1531-1540). IEEE. Sagiroglu, S., Sinanc, D. (2013, May). Big data: A review. InCollaboration Technologies and Systems (CTS), 2013 International Conference on(pp. 42-47). IEEE. Tene, O., Polonetsky, J. (2012). Big data for all: Privacy and user control in the age of analytics.Nw. J. Tech. Intell. Prop.,11, xxvii. Wu, X., Zhu, X., Wu, G. Q., Ding, W. (2014). Data mining with big data.IEEE transactions on knowledge and data engineering,26(1), 97-107.