Questões Militares de Inglês - Sinônimos | Synonyms

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    A number of writers in our field have criticized the concept of language teaching methods. Some say that methods are prescriptions for classroom behavior (Pennycook 1989); others that teachers do not think about methods when planning their lessons (Long 1991), and that methodological labels tell us little about what really occurs in classrooms (Katz 1996).

    A particular method can be imposed on teachers by others. However, we also know that teaching is more than following a recipe. Any method is going to be shaped by a teacher’s own understanding, beliefs, style, and level of experience. After all, teachers are professionals who can, in the best of all worlds, make their own decisions. They are informed by their own experience, the findings from research, and the wisdom of practice accumulated by the profession (see, for example, Kumaravadivelu 1994).

    Furthermore, a method is decontextualized. How a method is implemented in the classroom is going to be affected not only by who the teacher is, but also by who the students are, the institutional constraints and demands, and factors connected to the wider sociocultural context where the instruction takes place. In addition, decisions that teachers make are often affected by exigencies in the classroom rather than by methodological considerations. Saying that a particular method is practiced certainly does not give us the whole picture of what is happening in the classroom. Then, too, since a method is more abstract than a teaching activity, it is not surprising that teachers think in terms of activities rather than methodological choices when they plan their lessons.

    [...] Some language teaching methods share the view that language can best be learned when it is taught through communication, rather than for it; and second, that language acquisition can be enhanced by working not only on language, but also on the process of learning (learnng strategies, cooperative learning and multiple intelligences).

(LARSEN FREEMAN, D. Techniques and principles in language teaching. 2th ed. Oxford: Oxford University Press, 2000. pp. xi-xii. Adaptado)

How facial recognition technology aids police

Police officers’ ability to recognize and locate individuals with a history of committing crime is vital to their work. In fact, it is so important that officers believe possessing it is fundamental to the craft of effective street policing, crime prevention and investigation. However, with the total police workforce falling by almost 20 percent since 2010 and recorded crime rising, police forces are turning to new technological solutions to help enhance their capability and capacity to monitor and track individuals about whom they have concerns.

One such technology is Automated Facial Recognition (known as AFR). This works by analyzing key facial features, generating a mathematical representation of them, and then comparing them against known faces in a database, to determine possible matches. While a number of UK and international police forces have been enthusiastically exploring the potential of AFR, some groups have spoken about its legal and ethical status. They are concerned that the technology significantly extends the reach and depth of surveillance by the state.

Until now, however, there has been no robust evidence about what AFR systems can and cannot deliver for policing. Although AFR has become increasingly familiar to the public through its use at airports to help manage passport checks, the environment in such settings is quite controlled. Applying similar procedures to street policing is far more complex. Individuals on the street will be moving and may not look directly towards the camera. Levels of lighting change, too, and the system will have to cope with the vagaries of the British weather.

[…]

As with all innovative policing technologies there are important legal and ethical concerns and issues that still need to be considered. But in order for these to be meaningfully debated and assessed by citizens, regulators and law-makers, we need a detailed understanding of precisely what the technology can realistically accomplish. Sound evidence, rather than references to science fiction technology --- as seen in films such as Minority Report --- is essential.

With this in mind, one of our conclusions is that in terms of describing how AFR is being applied in policing currently, it is more accurate to think of it as “assisted facial recognition,” as opposed to a fully automated system. Unlike border control functions -- where the facial recognition is more of an automated system -- when supporting street policing, the algorithm is not deciding whether there is a match between a person and what is stored in the database. Rather, the system makes suggestions to a police operator about possible similarities. It is then down to the operator to confirm or refute them.

By Bethan Davies, Andrew Dawson, Martin Innes (Source: https://gcn.com/articles/2018/11/30/facial-recognitionpolicing.aspx, accessed May 30^th, 2020)

How facial recognition technology aids police

Police officers’ ability to recognize and locate individuals with a history of committing crime is vital to their work. In fact, it is so important that officers believe possessing it is fundamental to the craft of effective street policing, crime prevention and investigation. However, with the total police workforce falling by almost 20 percent since 2010 and recorded crime rising, police forces are turning to new technological solutions to help enhance their capability and capacity to monitor and track individuals about whom they have concerns.

One such technology is Automated Facial Recognition (known as AFR). This works by analyzing key facial features, generating a mathematical representation of them, and then comparing them against known faces in a database, to determine possible matches. While a number of UK and international police forces have been enthusiastically exploring the potential of AFR, some groups have spoken about its legal and ethical status. They are concerned that the technology significantly extends the reach and depth of surveillance by the state.

Until now, however, there has been no robust evidence about what AFR systems can and cannot deliver for policing. Although AFR has become increasingly familiar to the public through its use at airports to help manage passport checks, the environment in such settings is quite controlled. Applying similar procedures to street policing is far more complex. Individuals on the street will be moving and may not look directly towards the camera. Levels of lighting change, too, and the system will have to cope with the vagaries of the British weather.

[…]

As with all innovative policing technologies there are important legal and ethical concerns and issues that still need to be considered. But in order for these to be meaningfully debated and assessed by citizens, regulators and law-makers, we need a detailed understanding of precisely what the technology can realistically accomplish. Sound evidence, rather than references to science fiction technology --- as seen in films such as Minority Report --- is essential.

With this in mind, one of our conclusions is that in terms of describing how AFR is being applied in policing currently, it is more accurate to think of it as “assisted facial recognition,” as opposed to a fully automated system. Unlike border control functions -- where the facial recognition is more of an automated system -- when supporting street policing, the algorithm is not deciding whether there is a match between a person and what is stored in the database. Rather, the system makes suggestions to a police operator about possible similarities. It is then down to the operator to confirm or refute them.

By Bethan Davies, Andrew Dawson, Martin Innes (Source: https://gcn.com/articles/2018/11/30/facial-recognitionpolicing.aspx, accessed May 30^th, 2020)