Windhover By Hopkins Essay Example For Students

Windhover By Hopkins Essay In Gerard Manley Hopkins poem The Windhover there is a sort ofrepresentational allusion to Christ and Jesus. In other words the speakerpraises the Lord by praising what he takes as a symbol for Christ, the windhoverhimself. Through out the poem the speaker symbolizes Christs glory by the waythe falcon reacts to the air how it maneuvers and even charcteristic traits ofthe falcon species. One could only appreciate the glory of the Lord more afterinterpreting the poem. The poem is subtitled To Christ our Lordbecause the falcon reminds him of Christ. We will write a custom essay on Windhover By Hopkins specifically for you for only $16.38 $13.9/page Order now The speaker continuously hails one ofGods most stunning creatures, the falcon. He is flabbergasted at themagnificence of the windhovers flight. He wonders at its colorful feathers andthe sheer speed of its flight. His tone suggests that he is in awe. ..he isobserving something equivalent second coming of Jesus or angels walking amongregular men. He throws out a barrage visual imagery to try to describe thewindhover and still does not seem to come close to its real magnificence. Hewonders how such a creature could exist but is eventually just filled with gleein knowing the fact that it does exist. In the first stanza the speaker statesthat he spotted the mornings minion as if to suggest that the falcon was somehow subservient to the morning. He suggests that there is some sort of royalheiarchy by using words that recall images of sovereignty. Once the readerscratches the surface of the first stanza he can begin to understand theremainder of the poem. The second stanza takes a different stance on things. Thewindhover is out maneuvering when a smoothly and suddenly dives. The speakers isscared for the birds safety but is pleasantly surprised when the bird is liftedby a huge wind. One can say that in times of foolish pleasure he can fall butChrist will always lift be there to lift him back up. Christ is thus the cushionneeded for even a temporary fall from grace. Stanza three uses a barrage ofdescriptive words to denote the dignity of such a creature. In the animalkingdom it would be considered king of the roost. The speaker call the windhovera chevalier meaning knight or in other words a savior. Christ is also considereda savior. The speaker compares the bird and Christ with the hard work of theplow that creates a furrow and displays the wet soil underneath and burnedembers that shine red-gold when split open and burn with fire. That is directlycomparable to assumption that the speaker was leading a dark life until the Lordstirred up his life, split open his dark shell and helped him to shine with anew vigor for life. Christ could be seen in nature in the windhovers existence. He is symbolized in all the actions of the falcon and also represented in itscharactaeristics. The speaker praises the Lord by his amazed praise andrepresented in its characteristics. The speaker praises the Lord by his amazedpraise and appreciation. What he seems to be saying is that Christ exists ineven the smaller details in life and all we have to do is observe themperiodically to know that Christ lives on.

Han dynasty essays

Han dynasty essays The Han dynasty (202 BC - AD 220) reunited the China after the Qin dynasty fell apart. The Han ruled China for forty years, which was divided into two periods: the earlier period Western Han and the later period Easter Han. Gaozu, who was the first king of the Han dynasty, was a minor official in Qin dynasty. He became a leader of a small group of soldiers and acquired territories. Overtime, his army expanded to large number. In 206 BC, Gaozu took the title as King of Han and he ended the Qin dynasty in 202 BC.  ¡The Han period was, for good reason, associated with the victory of Confucianism. Where the Qin had given political support to Legalism, the Han gave it to Confucianism. ¡ (Ebrey, P. 75) After the Qin acrimonious governing, everyone welcomed Confucianism because the basis of Confucian ethics was the concept of  ¡love ¡ or  ¡goodness ¡. The Han was one of most remarkable and proud period in Chinese History. The Chinese displayed their pride from Han ¡s accomplishment by naming themselves the  ¡Han people ¡. During Han times, the Chinese extended the size of the state and population. Behind all the success of the Han dynasty, there was one of these people who took all the challenges and made the changes was the minister. Everyone thought that the cold, dark and hopeless winter was gone and now came a warm, bright and vigorous spring. Gaozu was their angel and rescued them from the hell of Qin dynasty, due to  ¡ Gaozu relax the harsh law of Qin, reduced the land tax, which under the Qin was said to have been as high as two-third of the total produce, and kept court expenditure at a minimum. ¡ (The Economic Order, P. 31). Under those policies, the population increased and the nation recovered with success. Because of this, the minister respected and admired Gaozu. He believed that Han dynasty would last forever and serve the government until he died. The minister did not care abou...

A Small Scale Sample Survey Essay Example | Topics and Well Written Essays - 1500 words

A Small Scale Sample Survey - Essay Example The sports centre should have modern amenities such as spacious gyms and air conditioned dance studios, several swimming pools and instructional pools, all aimed at facilitating it to offer Health and Fitness services to its clients (Bowers, 1970). It should therefore act as a place where the public can visit especially in the evenings, not only to improve health, but to make friends and to get fit with one's family as well as allowing their children to have fun (Bowers, 1970). Because of the foregoing, the researcher finds it necessary to investigate the sports centre to find out if it really satisfies these obligations. This survey therefore aims to investigate whether the Sports Centre carries out its mandate as stipulated in its manifesto. The objectives of this survey will thus be to investigate whether the sports centre operates within its mandate of offering sport and leisure courses to staff and students as well as the public. It will also attempt to find out whether the sports centre is capable of inspiring its members and non-members alike, sharing information with them about how they can become fitter and feel great at the centre. Finally, the survey will set out to investigate whether the sports Centre is an inclusive leisure facility offering competitive, instructional and leisure exercise opportunities to all who visit it. Discussion Since this is a small scale survey, the researcher proposes to come up with a questionnaire that will be used as the instrument of data collection. It is therefore the intention of the researcher to use a sample size and a sampling strategy that will best suit the purpose of this study. The Target population In this survey, the researcher wishes to target three categories of subjects in sampling his population. These include the staff, students and the public of the sports centre under investigation. These subjects are going to be selected because the researcher believes that they are better placed in giving the information that will help him to best investigate the sports centre. The staff and students will be involved in the study particularly because they are constantly in the sports centre and are thus able to learn the problems, if any affecting the sports centre. The public on the other hand will participate in the study because they are basically the ones who are the recipients of the bulk of services offered by the sports centre. They spent their money for the services offered. They may also decide whether to take their children to the sports centre or not, pay their fees or not, all depending on the satisfaction of the services they get. Thus this makes the public very decisive in their children's participation of the sports activities. The sampling strategy Through stratified random sampling, the researcher intends to select his sample population of about two hundred and ten subjects. In each of the three categories from which the sample population will be drawn, the researcher proposes to randomly select seventy respondents, that is seventy staff members, seventy students and seventy members of the public. Half of these respondents in

Essay Example | Topics and Well Written Essays - 500 words - 218

Essay Example In addition to this, the book offers the guidance that is helpful to the students involved in academic writing for the purposes of the summary of the ideas and facts in a book (Gerald, Birkenstein, and Russel, 117). An academic writer will in this instance be able to sharpen his or her ideas. Bright ideas will make him or her learn the ways that can enable him or her express him or herself before others by using the original ideas from his or her mind. As a result, the academic writer, in this case, will develop a paper that is free from plagiarism (Gerald, Birkenstein, and Russel, 128). Gerald Graff and Cathy Birkenstein consider academic writing as a recent research that outlines the processes used in writing through use of short chapters and understandable languages. In this way, the authors argue that academic writing will publish quality materials through use of these elements (Gerald, Birkenstein, and Russel, 145) Since the implementation of the Manitoba’s education policies in the Canadian education system, performance of the science and math’s related subjects has the worst record that also still continues to deteriorate as time continues to elapse (Behiels, 69). The results take place despite Manitoba spending on each K-12 student than any province in the country apart from Alberta (Levin, 74). Even the average student today can’t handle these subjects as was before since the introduction of the policies in the curriculum of the Canadian education. In this instance, the education authorities in the country exercised the mediocrity of the highest order in implementing the Manitoba education policies (Behiels, 87). The reason for this explanation of their level of mediocrity is that they implemented the policies without evaluating their impacts on the children. In addition to this, the officials also seem that received some bribery to ensure the implementation of the wro ng education policies in the system of Canadian education. As a result, it

Crime Prevention and Social Complexity of Crime Essay

Crime Prevention and Social Complexity of Crime - Essay Example In other words it can be understood that crime is very much a human act and if we take out the civilization clause from the dictionary of human society and make it equivalent to the savagery, this crime is not exactly something which can be termed inhumane. It's something present in very nature of humans and they technically possess every characteristic of an animal. It is a threat that is comparable to anything that has been faced by the society in past but is actually a very intelligent form of threat that waits for the opportunity to transform its ability into an act of crime under the influence of desire. Hence this phenomenon of crime is basically an action which involves at least two human beings with one being the perpetrator and the other one is the victim. Crime prevention is another part of the solution that has to tackle the social complexity of crime. Though the legal procedures and enforcement agencies are very much present to redress the problem, they have miserably failed to provide something which will have some long term impact. They actually provide security either through prosecution or through prevention. Prosecution leads to arrest and a whole lot of legal procedures including the judgment and imprisonment. Prevention deals with stopping a criminal from committing something heinous. The option of committing a crime is to be closed. Hence the target issue is the creation the hindrance for a criminal through wide spread precautionary measures being implemented through every single home to any of the working place or public place present in the locality. The important point is to shield oneself from being a victim. The crime and its different techniques have to be made understood to each and every person. Right from the begin ning i.e., during childhood, one should be made aware of the prevention procedures and the importance of it has to be made a part of the complete thought process. But still after this much precaution the outcome of these procedures has been found to be very much limited and the crime rate is on its way to rise and rise. The most important thing is to act against the cause that make a criminal rather than reducing the opportunities for him to commit some crime. We have to realize that this criminal has been developed from this society only and the problem is in the social pattern and due to these patterns we have to face certain people who have got out of the normal way of social life and are acting against the group of which it is a very important part. So the new crime prevention should deal with the very cause of creation of a criminal and factors fuelling its growth. Crime Prevention Plan of the new society The humans have reached to the current age of information after getting a number of destruction and wars. Initially, it had to fight adversities of earth and its surroundings and after the formation of some civilization, it

System to Filter Unwanted Messages from OSN User Walls

System to Filter Unwanted Messages from OSN User Walls M.Renuga Devi, G.Seetha lakshmi, M.Sarmila Abstract—One fundamental issue in today’s Online Social Networks (OSNs) is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Up to now, OSNs provide little support to this requirement. To fill the gap, in this paper, we propose a system allowing OSN users to have a direct control on the messages posted on their walls. This is achieved through a flexible rule-based system, that allows users to customize the filtering criteria to be applied to their walls, and a Machine Learning-based soft classifier automatically labeling messages in support of content-based filtering. 1. INTRODUCTION ONLINE Social Networks (OSNs) are today one of the most popular interactive medium to communicate, share, and disseminate a considerable amount of human life information. Daily and continuous communications imply the exchange of several types of content, including free text, image, audio, and video data. According to Facebookstatistics1 average user creates 90 pieces of content each month, whereas more than 30 billion pieces of content (web links, news, stories, blog posts, notes, photo albums, etc.) are shared each month. OSNs there is the possibility of posting or commenting other posts on particular public/private areas, called in general walls. Face book allows users to state who is allowed to insert messages in their walls (i.e., friends, friends of friends, or defined groups of friends). The aim of the present work is therefore to propose and experimentally evaluate an automated system, called Filtered Wall (FW), able to filter unwanted messages from OSN user walls. We exploit Machine Learning (ML) text categorization techniques. The major efforts in building a robust short text classifier (STC) are concentrated in the extraction and selection of a set of characterizing and discriminant features. We base the overall short text classification strategy on Radial Basis Function Networks (RBFN) for their proven capabilities in acting as soft classifiers, in managing noisy data and intrinsically vague classes. We insert the neural model within a hierarchical two level classification strategy. In the first level, the RBFN categorizes short messages as Neutral and Non-neutral; in the second stage, Non-neutral messages are classified producing gradual estimates of appropriateness to each of the considered category. The system provides a powerful rule layer exploiting a flexible language to specify Filtering Rules (FRs). In addition, the system provides the support for user-defined Black Lists (BLs), that is, lists of users that are temporarily prevented to post any kind of messages on a user wall. 2. RELATED WORK The main contribution of this paper is the design of a system providing customizable content-based message filtering for OSNs, based on ML techniques. As we have pointed out in the introduction, to the best of our knowledge, we are the first proposing such kind of application for OSNs. However, our work has relationships both with the state of the art in content-based filtering, as well as with the field of policy-based personalization for OSNs and, more in general, web contents. 2.1 Content-Based Filtering Information filtering systems are designed to classify a stream of dynamically generated information dispatched asynchronously by an information producer and present to the user those information that are likely to satisfy his/her requirements. In content-based filtering, each user is assumed to operate independently. As a result, a content-based filtering system selects information items based on the correlation between the content of the items and the user preferences as opposed to a collaborative filtering system that chooses items based on the correlation between people with similar preferences. Documents processed in content-based filtering are mostly textual in nature and this makes content-based filtering close to text classification. Single label, binary classification, partitioning incoming documents into relevant and non-relevant categories. More complex filtering systems include multi label text categorization automatically labeling messages into partial thematic categories. Content-based filtering is mainly based on the use of the ML paradigm according to which a classifier is automatically induced by learning from a set of pre-classified examples. Several experiments prove that Bag-of-Words (BoW) approaches yield good performance and prevail in general over more sophisticated text representation that may have superior semantics but lower statistical quality. The application of content-based filtering on messages posted on OSN user walls poses additional challenges given the short length of these messages other than the wide range of topics that can be discussed. 3. FILTERED WALL ARCHITECTURE The architecture in support of OSN services is a three-tier structure (Fig. 1). The first layer, called Social Network Manager (SNM), commonly aims to provide the basic OSN functionalities (i.e., profile and relationship management), whereas the second layer provides the support for external Social Network Applications (SNAs).The supported SNAs may in turn require an additional layer for their needed Graphical User Interfaces (GUIs). The core components of the proposed system are the Content-Based Messages Filtering (CBMF) and the Short Text Classifier modules. The latter component aims to classify messages according to a set of categories. In contrast, the first component exploits the message categorization provided by the STC module to enforce the FRs specified by the user. The possible final publication can be summarized as follows: 1. After entering the private wall of one of his/her contacts, the user tries to post a message, which is intercepted by FW. 2. A ML-based text classifier extracts metadata from the content of the message. 3. FW uses metadata provided by the classifier, together with data extracted from the social graph and users’ profiles, to enforce the filtering and BL rules. 4. Depending on the result of the previous step, the message will be published or filtered by FW. 4. SHORT TEXT CLASSIFIER Established techniques used for text classification work well on data sets with large documents such as newswires corpora but suffer when the documents in the corpus are short. In this context, critical aspects are the definition of a set of characterizing and discriminant features allowing the representation of underlying concepts and the collection of a complete and consistent set of supervised examples. We approach the task by defining a hierarchical two-level strategy assuming that it is better to identify and eliminate â€Å"neutral† sentences, and then classify â€Å"non-neutral† sentences. The first-level task is conceived as a hard classification in which short texts are labeled with crisp Neutral and Non-neutral labels. The second-level soft classifier acts on the crisp set of non-neutral short texts. 4.1 Text Representation The extraction of an appropriate set of features by which representing the text of a given document is a crucial task strongly affecting the performance of the overall classification strategy. We consider three types of features, BoW, Document properties (Dp) and Contextual Features (CF). Text representation using endogenous knowledge has a good general applicability; however, in operational settings, it is legitimate to use also exogenous knowledge, i.e., any source of information outside the message body but directly or indirectly related to the message itself. We introduce CF modeling information that characterizes the environment where the user is posting. These features play a key role in deterministically understanding the semantics of the messages. In the BoW representation, terms are identified with words. Dp features are heuristically assessed; their definition stems from intuitive considerations, domain specific criteria and in some cases required trial-and-error procedures. Bad words: They are computed similarly to the correct words feature, where the set K is a collection of â€Å"dirty words† for the domain language. Correct words: It expresses the amount of terms tk 2 T K, where tk is a term of the considered document dj and K is a set of known words for the domain language. Capital words: It expresses the amount of words mostly written with capital letters, calculated as the percentage of words within the message, having more than half of the characters in capital case. Punctuations characters: It is calculated as the percentage of the punctuation characters over the total number of characters in the message. For example, the value of the feature for the document â€Å"Hello!!! How’re u doing?† is 5/24. Exclamation marks: It is calculated as the percentage of exclamation marks over the total number of punctuation characters in the message. Referring to the aforementioned document, the value is 3/5. Question marks: It is calculated as the percentage of question marks over the total number of punctuations characters in the message. Referring to the aforementioned document, the value is 1/5. 4.2 Machine Learning-Based Classification We address short text categorization as a hierarchical two level classification process. The first-level classifier performs a binary hard categorization that labels messages as Neutral and Non-neutral. The first-level filtering task facilitates the subsequent second-level task in which a finer-grained Classification is performed. The second-level classifier performs a soft-partition of Non-neutral messages assigning a given message a gradual membership to each of the non-neutral classes. Among the variety of multiclass ML models well suited for text classification, we choose the RBFN model for the experimented competitive behavior with respect to other state-of-the-art classifiers. RFBNs have a single hidden layer of processing units with local, restricted activation domain: a Gaussian function is commonly used, but any other locally tunable function can be used. RBFN main advantages are that classification function is nonlinear, the model may produce confidence values and it may be robust to outliers; drawbacks are the potential sensitivity to input parameters, and potential overtraining sensitivity. The first-level classifier is then structured as a regular RBFN. In the second level of the classification stage, we introduce a modification of the standard use of RBFN. The collection of pre-classified messages presents some critical aspects greatly affecting the performance of the overall classification strategy. To work well, a ML-based classifier needs to be trained with a set of sufficiently complete and consistent pre-classified data. The difficulty of satisfying this constraint is essentially related to the subjective character of the interpretation process with which an expert decides whether to classify a document under a given category. A quantitative evaluation of the agreement among experts is then developed to make transparent the level of inconsistency under which the classification process has taken place. 5. FILTERING RULES AND BLACKLIST MANAGEMENT In this section, we introduce the rule layer adopted for filtering unwanted messages. We start by describing FRs, and then we illustrate the use of BLs. In what follows, we model a social network as a directed graph, where each node corresponds to a network user and edges denote relationships between two different users. In particular, each edge is labeled by the type of the established relationship (e.g., friend of, colleague of, parent of) and, possibly, the corresponding trust level, which represents how much a given user considers trustworthy with respect to that specific kind of relationship the user with whom he/ she is establishing the relationship. 5.1 Filtering Rules In defining the language for FRs specification, we consider three main issues that, in our opinion, should affect a message filtering decision. First of all, in OSNs like in everyday life, the same message may have different meanings and relevance based on who writes it. As a consequence, FRs should allow users to state constraints on message creators. Given the social network Scenario, creators may also be identified by exploiting information on their social graph. Definition 1 (Creator specification): A creator specification creator Spec implicitly denotes a set of OSN users. It can have one of the following forms, possibly combined. Definition2 (Filtering rule): A filtering rule FR is a tuple (author, creator Spec, content Spec, action), where author is the user who specifies the rule; creator Spec is a creator specification, specified according to Definition 1: Content Spec is a Boolean expression defined on content constraints of the form à °C; mlÞ, where C is a class of the first or second level and ml is the minimum membership level threshold required for class C to make the constraint satisfied; action 2fblock; notifying denotes the action to be performed by the system on the messages matching content Spec and created by users identified by creator Spec. In general, more than a filtering rule can apply to the same user. A message is therefore published only if it is not blocked by any of the filtering rules that apply to the message creator. Note moreover, that it may happen that a user profile does not contain a value for the attribute(s) referred by a FR (e.g., the profile does not specify a value for the attribute Hometown whereas the FR blocks all the messages authored by users coming from a specific city). 5.2 Online Setup Assistant for FRs Thresholds As mentioned in the previous section, we address the problem of setting thresholds to filter rules, by conceiving and implementing within FW, an Online Setup Assistant procedure. 5.3 Blacklists A further component of our system is a BL mechanism to avoid messages from undesired creators, independent from their contents. BLs are directly managed by the system, which should be able to determine who are the users to be inserted in the BL and decide when users retention in the BL is finished. To enhance flexibility, such information are given to the system through a set of rules, hereafter called BL rules. Such rules are not defined by the SNMP; therefore, they are not meant as general high-level directives to be applied to the whole community. Similar to FRs, our BL rules make the wall owner able to identify users to be blocked according to their profiles as well as their relationships in the OSN. Therefore, by means of a BL rule, wall owners are, for example, able to ban from their walls users they do not directly know (i.e., with which they have only indirect relationships), or users that are friend of a given person as they may have a bad opinion of this person. 6. EVALUATION In this section, we illustrate the performance evaluation study we have carried out the classification and filtering modules. We start by describing the data set. 6.1 Problem and Data Set Description The analysis of related work has highlighted the lack of an publicly available benchmark for comparing different approaches to content-based classification of OSN short texts. 6.2 Short Text Classifier Evaluation 6.2.1 Evaluation Metrics Two different types of measures will be used to evaluate the effectiveness of first-level and second-level classifications. In the first level, the short text classification procedure is evaluated on the basis of the contingency table approach. In particular, the derived well-known Overall Accuracy (OA) index capturing the simple percent agreement between truth and classification results, is complemented with the Cohen’s KAPPA (K) coefficient thought to be a more robust measure taking into account the agreement occurring by chance . At second level, we adopt measures widely accepted in the Information Retrieval and Document Analysis field, that is, Precision (P), that permits to evaluate the number of false positives, Recall (R), that permits to evaluate the number of false negatives, and the overall metric F-Measure (F_), defined as the harmonic mean between the above two indexes. 6.2.2 Numerical Results By trial and error, we found a quite good parameter configuration for the RBFN learning model. The best value for the M parameter, that determines the number of Basis Function, is heuristically addressed to N=2, where N is the number of input patterns from the data set. 6.2.3 Comparison Analysis The lack of benchmarks for OSN short text classification makes problematic the development of a reliable comparative analysis. However, an indirect comparison of our method can be done with work that show similarities or complementary aspects with our solution. 6.3 Overall Performance and Discussion In order to provide an overall assessment of how effectively the system applies a FR. This table allows us to estimate the Precision and Recall of our FRs, Let us suppose that the system applies a given rule on a certain message. In contrast, Recall has to be interpreted as the probability that, given a rule that must be applied over a certain message, the rule is really enforced. Results achieved by the content-based specification component, on the first-level classification, can be considered good enough and reasonably aligned with those obtained by well-known information filtering techniques. 7. DICOMFw DicomFW is a prototype Face book application8 that emulates a personal wall where the user can apply a simple combination of the proposed FR’s. Throughout the development of the prototype, we have focused our attention only on the FRs, leaving BL implementation as a future improvement. However, the implemented functionality is critical, since it permits the STC and CBMF components to interact. To summarize, our application permits to 1. View the list of users’ FWs; 2. View messages and post a new one on a FW; 3. Define FRs using the OSA tool. When a user tries to post a message on a wall, he/ she receive an alerting message if it is blocked by FW. 8 CONCLUSIONS In this paper, we have presented a system to filter undesired messages from OSN walls. The system exploits a ML soft classifier to enforce customizable content-dependent FR’s. Fig. 3. DicomFW: A message filtered by the wall’s owner FRs We plan to study strategies and techniques limiting the inferences that a user can do on the enforced filtering rules with the aim of bypassing the filtering system, such as for instance randomly notifying a message that should instead be blocked, or detecting modifications to profile attributes that have been made for the only purpose of defeating the filtering system. REFERENCES [1] A. Adomavicius and G. Tuzhilin, â€Å"Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions,† IEEE Trans. Knowledge and Data Eng., vol. 17, no. 6, pp. 734-749, June 2005. [2] M. Chua and H. Chen, â€Å"A Machine Learning Approach to Web Page Filtering Using Content and Structure Analysis,† Decision Support Systems, vol. 44, no. 2, pp. 482-494, 2008.

The Medias Degradation of Women Essay -- Media Exploitation of Women

Women have been fighting for the right to be equal members of society for centuries. In the past women were treated as second class citizens and didn’t have the same rights as men did. Women later lead a movement to change these ways. Although some drastic changes did come about from these movements, equality wasn’t fully attained. In this day and age, equality between men and women still hasn’t been achieved and the media is to blame for that. For decades, the media has dominated society’s views and perspectives of others. Due to recent media, it has been difficult to regulate how women are being influenced and treated by other people in society. The media influences society tremendously and subconsciously steers the way we treat and think of others. Advertisements, television shows, movies, the internet, magazines and other forms of the media have all targeted women in a very erroneous manner. Women are still being highly misrepresented and misunderstood through media all over the world. Increasingly, real women are being under represented, misrepresented, sexualized, discriminated, stereotyped and in many cases violence and abuse against women has also been glamorized. Although we feel that we’ve come a long way, women still aren’t being treated as equal members of society. Going back to the 1950’s, women were expected to be stay at home mothers and housewives. â€Å"This was also the era of the "happy homemaker." For young mothers in the 1950s, domesticity was idealized in the media, and women were encouraged to stay at home if the family could afford it. Women who chose to work when they didn't need the paycheck were often considered selfish, putting themselves before the needs of their family† (Daniels 2002)... ...resentation. DVD. Dallas, TX: Assemble. Retrieved May 5, 2014(http://film.missrepresentation.org/) Research Article) Silverstein, Brett. 1996. "The Role of the Mass Media in Promoting a Thin Standard of Bodily Attractiveness for Women." Sex Roles:519-520. Retrieved May 6, 2014(http://link.springer.com/article/10.1007/BF00287452#page-1) (Research Article) Stankiewicz, Julie. 2008. "Women as sex objects and victims in print advertisements." Sex Roles:579-589. Retrieved May 5, 2014(http://www.skidmore.edu/classics/courses/2011spring/gw101/Women%20As%20S ex%20 Objects%20and%20Victims%20in%20Print%20Advertisements.pdf) (Research Article) Wood, Julia. 1994. "Gendered Media: The Influence of Media on Views of Gender." Gendered Lives: Communication, Gender, and Culture:231-244. Retrieved May 6, 2014(http://www.udel.edu/comm245/readings/GenderedMedia.pdf)