INTRODUCTION

At the outset, mappings between one language and another can seem relatively straightforward. For instance, the English thank you corresponds rather directly to the French merci. However, cultural conventions and the communicative context can influence the interpretation of what are seemingly straightforward utterances. An English speaker often uses a simple thank you to accept an offer of food. Conversely, a French speaker uses merci to refuse an offer of food (Crystal 2010). In an Anglo context, failing an offer of food, a hungry individual in a kitchen might say something smells good to solicit such an offer. A Malagasy individual in search of a free meal would ask iona no maska: ‘what’s cooking?’ (Myers-Scotton 2006). Cultures and contexts provide varying expectations as to how speakers use and interpret linguistic signs. They also guide the degree to which individuals use direct or indirect messages to accomplish goals.

It is at the level that might be called ‘reading between the lines’ that cultural differences may arise and these may contribute to misunderstandings in intercultural communication. For instance, Bailey (2001) has shown how interactions between Korean American shop owners and African American customers in Los Angeles may result in misunderstandings. Korean American shop owners most typically focus on the transaction at hand whereas African Americans view these interactions as an opportunity to reaffirm relationships through small talk. When the Korean Americans do not reciprocate, the African Americans perceive the shop owners to be unfriendly and even racist. African Americans often confront them on this point and this only serves to frighten the shop owners and aggravate the situation.

INTRODUCTION

Variation in the organisation of writing across cultures has been studied from a number of perspectives. Givón (1983) developed a quantitative model for cross-language discourse analysis to measure topic continuity (thematic, action and topic/participant continuity) in a number of languages. Kaplan (1966, 1972, 1988) pioneered research in the area of contrastive rhetoric (also known as contrastive discourse analysis) by examining variation in the organisation of writing by writers from different language/cultural traditions (see also Connor & Kaplan 1987). Connor (2008, 2011) and Connor, Nagelhout and Rozycki (2008) have introduced the term ‘intercultural rhetoric’ to underscore the global orientation of their recent research in this area.

Research in the field of genre analysis (Swales, 1990, 2004; Bhathia 1993, 2004) and corpus analysis (Johansson 1998) has also recently started to include writing produced by researchers writing in a second language as a means of global communication.

The field of discourse analysis has developed in other important ways over the past three decades, emphasising the importance of social context, including variables such as audience and purpose; processes such as revision and collaboration; and interactional aspects of writing, such as expectations of a particular discourse community, the latter explored in the work of Fairclough (1992), Gee (1999, 2005) and Hyland (2000, 2004, 2005, 2009). Analysis of the use of particular textual elements has also developed fresh perspectives – for example, the studies reported in Hyland and Sancho-Guinda’s (2012) edited volume Stance and Voice in Written Academic Genres.

This chapter focuses on how you can reflect on your practice and engage in ongoing professional learning as a language and literacy teacher. We are working on the assumption that you think of yourself as an intellectual (Giroux 1988) who is critically engaged in your work, even though it can be incredibly difficult to maintain such a stance at the current moment, when teachers are being put under enormous pressure to improve educational outcomes. The emphasis placed by standards-based reforms, as proposed by Linda Darling-Hammond (2004), on improving performance on the part of both teachers and their students can sometimes undermine teachers’ capacity to critically reflect on their teaching, especially when they feel pressured to ‘teach to the test’ in order to improve their students’ results in standardised tests such as NAPLAN.

Yet a moment’s reflection is enough to recognise the importance of teachers affirming their status as intellectuals and engaging in inquiry that might provide a perspective on such reforms.

INTRODUCTION

People fill a variety of roles in society and these roles come with certain expectations. For instance, medical doctors are expected to provide care for patients in medical contexts. The role ‘doctor’ is established by institutional conventions and societal expectations (Cordella 2004; see also Goffman 1959). Doctors also fill their role because they are more knowledgeable about the medical context. This knowledge includes knowledge of the topics at stake as well as the style of language used to discuss these topics. The role of the doctor, as well as the knowledge associated with this role, gives doctors some power over patients in the medical context.

Similar observations may be made about the respective roles of managers and subordinates in business contexts, legal professionals and clients in legal contexts, teachers and students in educational contexts, and so on. In sum, roles in society emerge because of institutional conventions, societal expectations and the possession of knowledge. Furthermore, many of these roles (e.g. doctors, legal professionals, teachers) are imbued with power over other contextually related roles (e.g. patients, clients, students). As social agents, we acquire these roles by gaining knowledge and these roles grant us certain powers over others. Historical circumstances often influence our ability to construct these roles. For instance, speakers of non-standard English varieties are often disadvantaged when entering the mainstream school system, which favours Standard English.

Australia has, for several decades, espoused multiculturalism, although this rhetoric has now been shaken by the controversies that surround refugees. Even so it remains the case that educational policy and practice in Australia have variously acknowledged the diverse cultures and languages of students in schools.

Recently there has been a pronounced shift away from deficit constructions of students from language backgrounds other than English to teachers recognising and drawing on the rich cultural and linguistic resources, often called ‘funds of knowledge’, attributed to the work of Luis Moll, Cathy Amanti, Deborah Neff and Norma Gonzalez (Moll & Amanti et al. 1992). As a literacy educator, you will typically find yourself in classrooms that reflect a diversity of cultures and languages. Within such settings, issues associated with multiculturalism and the flow of people around the world are not simply topics for debate, but matters that you and your students negotiate each day. This is often a richly rewarding experience, but it can involve challenges that cause you to interrogate your own values and beliefs, in much the same way that teachers like Rachel and Bella (see Chapter 2) were prompted to think about the way their lives have shaped their work as literacy educators.

In this chapter you will be hearing more from Thomas, and reflecting on the complex decisions he makes when planning for literacy learning and teaching. In addition, you will be presented with two other accounts of planning for learning and teaching: one by Gaelene that arises out of her work as a literacy teacher within a middle years context; the other by Maria about her experiences of whole-school planning within a primary school.

In 1906, the Warrens, a wealthy New York banking family, rented a summer house on Long Island. That summer, six people in the household came down with typhoid fever, a serious bacterial illness with a persistent and very high fever. In the era before antibiotics, typhoid was frequently deadly.

Although the Warrens all survived, the outbreak was troubling enough that a sanitary engineer named George Soper was hired to investigate. Soper examined the water supply, the plumbing, and other possible sources of contamination, but found nothing to explain the outbreak. Eventually, he investigated the family’s new cook, a woman named Mary Mallon. Soper went through her employment history, and found that there had been typhoid outbreaks in most of the places she had worked. Mary Mallon, who became known as “Typhoid Mary,” was the first documented example of an asymptomatic carrier of typhoid (Figure 1.1). She herself was not sick, but she was able to spread the disease to others. Once Mary was discovered to carry typhoid, she was quarantined in a hospital for most of the rest of her life.

In the four parts of this book we’ve introduced foundational concepts from computer science in the context of biology. We had a good time writing it, and hope you’ve enjoyed using it.

Over the course of the book you’ve learned some powerful and fundamental techniques that are used throughout computational biology. You’ve also learned a valuable general skill – how to design computational solutions and implement them in your own programs. Like other skills, computational problem-solving and programming benefit from practice. As you do more, you’ll get even better at it.

With that in mind, we hope that you come away from this book with the confidence to take on new problems. These might range from writing a short program to do some quick analysis, to interfacing with existing programs, to solving altogether new research problems. The key is to find ways to use these tools to further your own interests. In the process, perhaps you’ll join us in the excitement that arises when computational techniques are used to explore the many mysteries of life on Earth.

Our final task is to develop an algorithm to reconstruct phylogenetic relationships based on sequence data. In the final homework problem, the source sequences are mitochondrial DNA from a number of modern human individuals, as well as from several fossils, including a Neanderthal. Let us begin by saying something about these sequences and how they are used to create input for our algorithm.

The cells of eukaryotes, such as humans, contain two types of DNA. The largest type is the nuclear DNA which is found in sets of chromosomes that are inherited sexually, with one copy of each chromosome coming from either parent. A second type of DNA can be found in the mitochondria, organelles specializing in energy metabolism. Mitochondria contain their own circular DNA molecule. As it turns out, mitochondria are inherited maternally – individual humans get their mitochondria from their mother’s egg rather than their father’s sperm. Thus, mitochondrial DNA is passed along the maternal line only.

Mitochondrial DNA has frequently been used in studies of human evolution. One advantage is the fact that it’s inherited from a single parent, and thus is not subject to recombination. Another advantage is the fact that mutations arise comparatively quickly in mammalian mitochondrial DNA. If we are comparing closely related samples, such as human individuals, a higher rate of mutation is good because it produces more differences with which to distinguish the samples.

In the previous chapter we saw how to solve some important computational problems with the use-it-or-lose-it principle. This approach obtains the correct answer by effectively exploring every possible solution to a problem. Unfortunately, it turns out that this approach can get very slow as data sets get large. For example, on a typical personal computer, running the LCS function on two random strings, each of length 10, takes approximately one thousandth of a second. But on two strings of length 25 it takes a good part of an hour and on strings of length 100 (which is still very short by the standards of biologists working with real sequences) it would take, conservatively, well over a trillion years.

We began this part of the book with the problem of determining homology between the mammalian X and the bird Z chromosomes. To solve this problem, we’ll need to do over 1000 comparisons between proteins that are each hundreds of amino acids long. That will (almost literally) take forever!

The different cell types in the human body look different and do very different things: Compare, for example, liver cells and brain cells. How do they manage to be so different given that they have the same DNA? The answer is that cells regulate the expression of their genes – that is, they control when and where their genes are used to make protein. As a result, different cell types make a different complement of proteins.

In fact, the expression of a gene can be regulated by other genes. Biologists represent this using a gene regulatory network, a diagram that shows how genes interact. Figure 13.1 shows an example of such a network for some genes in the bacterium Bacillus subtilis. In the diagram, each gene is represented by a circular node. To show that one gene regulates another, we draw an edge, that is, a line with an arrow. This indicates that one gene (the one which the arrow is drawn from) regulates the transcription of the second (the one which the arrow is drawn to). The effect of this regulation might either be positive (upregulation) or negative (downregulation), but we won’t make a distinction between those two cases here.