Alright, so let's begin. We've been looking at quite a few codes right now. The last thing we looked at was ReadMiller codes. So let me just summarize as to where we are right now. Okay, so at this point, I think what we should be comfortable doing, open your door at the very end. You're okay? You don't want the fan. I don't know if you can hear me, but it's okay. Don't matter. So what we've been looking at is one of the various things we saw. We saw ReadMiller codes. So essentially this was where we got to and these two guys were very interesting from various points of view and ReadMiller codes and other interesting properties. But essentially what we can do there is given a block length and given p which is required of our correcting capability, we can come up with a code most probably a ReadSolomon or a PCH code which can achieve this. So these two can achieve for a given block length and error correcting capability. They can achieve some good code construction and in fact this is also good from a complexity point of view. The construction is easy to do then even the decoding is easy to do. So you have an algorithm which works. So the nice thing about ReadMiller codes is they're probably not as efficient as the ReadSolomon and PCH codes but they have some other properties. The decoder is even simpler than the ReadSolomon and PCH codes and they work very directly with the parity projects and all that and it's very intuitive and nice to decode. Then like I said the decoder that we used in the ReadMiller code can be extended for other things also and we'll see that in the next course. So this is where we are as far as the course is concerned and we have about three weeks to go two and a half to three weeks I think. So we're going to take what we're going to do in the next two to three weeks is the first thing we'll look at are a couple of issues like concatenated reflections. That's what we'll see today mostly it will be over today may not even take all of today. So after that we'll move on to an area for weight distribution and time permitting you might do something else after that. So after that maybe a little bit of more interesting stuff. So these two I want to do and with that I think more or less the course itself will be over and after that we'll worry about a few things and we're doing okay on time in case we are a little short to make those things. So this idea of concatenation is very bad post it's very crucial and even in modern codes they are used a lot for this notion of thinking of one code in terms of several other codes and what I'm going to do is talk about concatenations next. So the first kind of concatenation we'll talk about is what's known as concatenation. We're not really a concatenation. So I'm putting it into the general topic of concatenations because it falls into the category of bringing two different codes together and constructing a new code. So that's the idea of concatenations. So you bring two different codes together. So how do you do that is the idea and the concatenation. The first thing you'll see is the product code. Product code is quite simple. It's an interesting little idea. So what we do is we have two codes C1, N1, K1, D1, we have another code C2 and N2, K2, D2, we have two codes N1, K1, D1 and N2, K2, C2. So let's say G1 was the standard matrix of C1 and G2 was the standard matrix of C1. In the product construction what you do is you take so what you do is the product construction product of C1 and C2 will result in N1 times N2 comma K1 times K2 code. So we'll come back to the minimum distance later on but essentially the code will be N1, N2 and K1, K2. So that's where we call it the product. So the dimension gets multiplied, the blockchain gets multiplied. So this is the code that you're going to get. So the code essentially has K1, K2, message bits. So we'll think of the message as a matrix. So far we've been thinking of the message as a vector. You can also think of it as a matrix. In the product construction it's convenient to think of it as a matrix. You can of course also unwrap it and think of it as one big long vector if you want but the matrix is simple. So I'm going to have a message M which is K1 by K2. So to get a code word of the product code this message is K1 by K2 matrix. What's my code word going to be? K keeping with the same spirit. What will my code word be? How many bits are there in the code word? N1 and N2. So what is my code word going to be? N1 cross N2 matrix. So I want the N1 cross N2 matrix. I'm going to take this message matrix and do something with it and get a code word which is an N1 cross N2 matrix. So what I do is the following. So I'll take G1 transpose and multiply on the left side and then I'll take G2 and multiply on the right side. So that's what I'm going to do to get a N1 cross N2 matrix and this is essentially the product construction. So first of all this multiplication is very well defined. G1 transpose what's the dimensions of G1 transpose N1 cross K1. So that I can definitely multiply with an M which is N1 cross K2. And G2 is also K2 cross N2 and I do definitely get a N1 cross N2 matrix. So first of all is this product code a linear code which is linear. You take a message M1 produce a code word with it, take a message M2 produce a code word with it and then add the two what happens. You naturally get the code word corresponding to M1 plus M2 so it's linear. So that's it. This is linear. What is the next interesting question that we can ask about this code? The minimum distance. The rate may be what will be the rate. K1 K2 by N1 N2 product of the two rates. It's not too interesting. Minimum distance is not interesting. To get to the minimum distance there is one little property that we can do which is nice. So in this code word matrix let's look at the code word matrix a little bit more closely. N1 cross N2. It will have N1 rows and N2 columns. An arbitrary row of this matrix. What can I say about it? My goodness. A row of this matrix of this code word. The row of this matrix. Does it have any interesting property? Can you observe something from the way it was constructed? What will be the row? Sorry why? Yeah so it will be some code word of C2. So that's the first statement I want and then we will worry about the minimum distance later. So let's do a code word of you can do the multiplication, G1 transpose, N first remember matrix multiplication is associated. You can do it in any order. You will get the same answer. So you do the multiplication, G1 transpose, N first and you get some matrix and then you multiply by G2. So finally what you get will actually be a combination of the rows of G2 so clearly that has to belong to the code C. What about any column? The column will do a code word of C1. How do you get to that? You do the multiplication M times G2 first and then you multiply by G1 transpose on the left product you get column will be a linear combination of the columns of G1 transpose which is nothing but the rows of G1 and that has to be a code word of C. So it's just a basic matrix multiplication but we will get that answer. So this is a crucial property. So every row of the product code word is a code word of C2. Every column of a product code word is a code word of C1. So that's an advantage. That's a nice property to have for the product code word. So now we can think about the minimum distance. Let's talk about the minimum distance. So let's just tell you anything about the minimum distance. M1 D2? D1 is a code word of C1. Then there are also the minimum distance program that we have introduced. Let's look at it. Suppose somebody tells me there is a non-zero code word matrix. If somebody tells me there is a non-zero code word matrix there should be at least one column which is non-zero. If all columns are zero then you are finished. There should be at least one column which is non-zero. You go to that column. How many ones should be there in the column? At least D1. There should be at least D11 in that non-zero column. So now go to those D1 rows corresponding to the non-zero values in that column. Each of those D1 rows is non-zero and it's a code word of C2. So each of those D1 rows should have weight at least D2. So what should the overall weight be? At least D1 times D2. So that's the final result. So there is another way to view this multiplication which will complicate things a little bit. So typically we take G1 and G2 to be systematic form. We take them systematic form. So that when you do G1 transpose and G2 what will happen if you take G1 and G2 in systematic form? The code word will be M will be a top of it on the top K1 by K2 part. There will be a top K1 by K2 part. And then there will be a N minus K1 part N1 minus K1 part and N2 minus K2 part. So what's happening in the encoding? The first encoding M by G2 let's say. Then you will fill out all these parities. And then what are you doing? Encoding each column by G1. So we will be filling out all these parities. So usually people think of these parities as the row parities of M. And these parities as the column parities of M. And then what are these parities? They are parities on the parities. So if I describe it to you this way, it's a bit more complicated to quickly... Remember the other fact, every column is still a code word of C1. And every row is still a code word of C2. So it's a little bit more complicated to think of it that way. So you encode by C2 first and then encode by C1. It's not clear why every row should again be a code word of C2. So this multiplication works. So you can do it either way. So it has to be consistent in some way. So even these rows will be code words of C2. So it may not be immediately clear that that's the truth. So this is how the structure of the code word will look. So let's take some nice examples here. So one more for doing this example. Let's take some simple quotes. For instance, you have the 7, 4, 3, and encode. Except in some very strange cases, usually you take C1 to be equal to C2. So it's a very common situation. So nobody takes it. So you look at the product of C and C. What would be its parameters? 9, 16, 11 is equal to 9. So you have a 4 error correcting code of length 49.  What will happen? So directly if I constructed. So maybe 49 may not be used to it. Maybe length 63. Let's say length 63, DCH code of 4 error correcting. What will you have? What will be the error? What will be K? 63 comma, what will be K? 39. So you have to subtract 24. 9 comma greater than or equal to 9. This case is going to be equal to 9. I know that. So you need 24 parities. So if you try and shorten, what will happen? You can always shorten. When you shorten, you can go to 49. And then you have to subtract 24. So you will have 25. So if you construct it directly using the DCH, you have an advantage over the product code. Definitely the product code is not that interesting. From optimal dimensions for a given minimum distance point of view. At least in this example. In many examples also it could be true. So this is the situation. But then there are some other advantages to the product code. But remember that this can be a problem. Some simple stuff. So to improve your rate, maybe you want to take... This is the first example. Maybe you want to take C to be the 743 and then maybe you take C2 to be let's say 9, 8, 2, even 8, 4. So let's try that. Just for fun. Just to see how it works out. What's the product of C1 and C2? It's going to be 63. 22. So if I try to construct it directly by DCH, what will I get? If I want minimum distance let's say 5. So 5 is more reasonable. So let's T equals 2. We'll get even a 63. 51 code. So it's not that competitive. Maybe you want to try something else. Let's try something else. Let's take C1 to be 8, 4, 4 code. How will I get the 8, 4, 4 code? You can take the Hamming code and do an extension by 1. Or it's the same as the ReadMuller code. ReadMuller code at length 8. And let's say we just do C1. Let's just do C with C. 64. 16. Now that's a little bit more interesting. 16 is a large new distance. If you want to do a corresponding DCH code you can aim for a 63 code with length 15. And then maybe extend it and get this. Suppose you try to add then what will you get? DCH should be 63. 15. Remember this. T equals 7. And we know a lower bound under K for DCH. What's the lower bound? N minus MT. N is going to be 6. 6 into 7 is 42. 643 minus 42 is 11. So it's 21. In most cases it looks like the DCH code is going to be from a rate point of view better overall if you directly constrain. But the product code will have some advantage. So let me say what the advantage is. The advantage will be in the decoding. So there is a structure to the product code which the DCH code does not have. You can exploit that. That is basically that each column is a code word of a smaller code. You don't have to worry too hard about decoding. Each row is a code word of a smaller code. So you can take that row alone and do some suboptimal decoding and try to combine all of them together and play some tricks there. So those things you cannot do with the DCH code.  So that's where you can put the game. That's one thing. The other thing is finding soft input decoders for product codes is also easier. You keep it easier than finding infertile pieces. Those are advantages today. But let me try and motivate this decoder. So we'll look at the 7.4.3 Hamming code. So we'll go back to this original example. Product of 7.4.3 with itself. Let's try and come up with that decoder which will correct 4 errors. So let's see if it's possible or not. Let's try that. So decoding product code. So we'll do this by example. I'm never going to do it in great detail. So we'll take the 7.4.3 Hamming product of basically a product of 1916 product of 9 code. So you should be able to correct 4 errors. So from just a single error character. So let's look at the structure of the code. Basically a 7.7 code word. Each row is a code word of the Hamming code. Each column is a code word of the Hamming code. And you can have, suppose I can have any 4 errors. So this is a code word. Let's say this is a received word. So any 4 positions can be an error. So how can I, so is there any strategy that you can think of? Which is useful in correcting. Any ideas? How can I go about correcting errors? Let's say there are some T errors. We are in the received word. What is the strategy that you can use? How to use the product property? So you try to do it one row at a time or one column at a time. So that's the idea. So try and decode one row at a time. One column at a time. So now we will have some interesting combinations arising. So typically I want to correct the minimum distance capability. I want to be able to correct 4 error patterns. So if my 4 error patterns are like this then what will happen? So if I correct row wise I will be in trouble. But then what can I do? If I correct column wise I will be okay. I will be able to correct. So like this you can think of so many other ways in which these 4 errors can distribute over a 7 x 7 matrix. Is there any case in which I will never be able to correct either row wise or column wise? If you have the same column then my row decoder will correct only. There is some error. It's part of a column which has 4 errors and it's part of a row which also doesn't. There are only 4. Let's say I am looking at only 4. Maximum of 4. So we need to be in a shape like this. So any other shape is correct about. But if we form this shape what will happen? What will happen if we form this shape? Yeah so there will be trouble. Whether you go row wise or column wise you will never be able to correct it fully. So you have to combine both the row and the column. So what do you do? You go row wise and see which rows there are errors. So all the syndromes will evaluate to 0 except for 2 rows. The equation of columns all the syndromes will evaluate to 0 except for 2 columns. And then you have to do some additional row to think about what is the possibility. So if it is just 1 or 2. So there are so many cases. So you have to work it out combinatorially one after the other. So basically it's I think possible for this case you can list out case by case thing and correct that to whatever. I think it might be possible. So I am not very sure. So you should not decode. That's what I am saying. Just compute the syndromes all the row syndromes. Compute all the column syndromes. If you have only 1 row syndrome being non-zero. I mean so many combinations are possible. So you have to try and correct and then re-evaluate all the syndromes. So there are so many things you can do. So one thing you can do is look at all the rows. You compute all the syndromes and correct the rest just based on that. And then go through all the columns. Go through all the columns and then correct the rest based on that. Then go through all the rows. Keep iterating it till all the row syndromes are 0 and the column syndromes are 0. Keep on doing this iterative. Usually it should work except that these kind of cases may not work very well. So what will happen? If I do a row is what will happen? There are two rows. If you do the hamming correction what will happen? It will try and introduce another error somewhere. And these two will introduce another error here. You don't know how it will work out. So I think it should actually introduce in the same place. So it's a hamming code. It's the same code. So you get another error here. And then when you go column wise there are more errors to be introduced. And you keep on exploring.  You have to use your row iteration and column iteration together in the next iteration etc. So on the top of my head I don't know if there's an algorithm or not. But I believe you can come up with something which might be able to correct power for errors. So it might be an exhaustive more painful list than what I've been doing it. But you might be able to correct it. So essentially the idea is to iterate between row and column decoders. And this is quite powerful. So what will happen is when you do these kind of iterations you usually cannot guarantee an error correcting capability. You cannot say all errors are very T I might be able to correct. You just do a simple iteration. You won't be able to correct this pattern for instance. If you just do all the rows, all the columns and keep on doing it you will never be able to correct this pattern. But this pattern is kind of peculiar. It requires some very precise coordination between the way the row and column errors happen. But so many other patterns which have even more errors can be corrected. So many six other patterns can be corrected. It's not that it's a very sharp bounded distance decoder. It will be a strange non-bounded distance decoder. You can think of the combinatorics here. So many other errors you will be able to correct. And that's an advantage in practice several times. Even though you cannot precisely guarantee an error correcting capability, if you can only not correct very few error patterns, that's okay. Usually these things don't occur with very high probability. Probability will be low. It might be better. So these kind of ideas are powerful today in the modern probabilistic kind of decoding as opposed to the very bounded distance type of decoding. These kind of ideas are very popular. The nice thing is each iteration is not very painful. If you're just correcting one Hamming code, I mean how hard is it? It's not like you don't need any finite field or anything. Just quickly you can correct one Hamming code after the other. So component decoders are very simple. And you kind of do some iterations here and there using some particle code. Another crucial point I want you to observe is you can also write this code word out as a 49 length vector. So let's try and do that. If you write the code word as a 49 length vector, somebody c1, c1, c2, c1, c2, c1, c2, c2, c7, c7, c7, c7, c7, c7. So basically you write code word as a vector. So one nice property I have is that these guys belong to the what? 743 Hamming code. So sticking with the example. So each of these guys belong to the Hamming code. Likewise these guys also belong to the Hamming code. These guys also belong to the Hamming code. So basically this code word has some local structure. What do we mean by local? A few of the code word bits together have some structure with it. Overall the code itself has some structure and that might be a very long code word you may not be interested in exploiting the overall code structure. But locally there might be some nice structure which you can quickly explore. And there is some merit in it. Particularly if you can iterate between these local structures and then try to combine them in some global way if you can or even just iterate blindly. Actually the global structure will begin to asset itself. So iterating but you have to combine them carefully and then you will bring in the thing together. So this kind of idea is very powerful today. So in today's modern interpretation you use some local structure in the code word and then try and iterate and get to your advantage. So this product code is a very simple way in which you can bring in local structure. So it's not so efficient but it's nice. So there are also other local structures. For instance these words together they also have some structure. So you kind of interlace these local structures and then you get some more interesting ideas coming up. Alright so you can definitely generalize these decoders. You can generalize this decoder and construct some more general decoders for the N1, K1, K1 case. But usually you may not be able to guarantee that you can correct up to the error correcting capability. You may not be able to guarantee that but what will be true? You will be able to correct a significant fraction of the errors. Maybe 1 or 2 where ever you may not be able to correct depending on the pattern. If you don't care about it, it will be over. You can implement the decoder. Yes. Yeah. Yeah. Yeah, you can do that. You can write down a particular matrix for this also. Overall, combine it with a big matrix. See the problem is, well it won't scale. That's the problem. Small numbers you can do it. But when you go to like, you want to take a product of two big codes and you may not be able to do it. Yes. I didn't say it can always be corrected. I said there might be some patterns before which you may not be able to correct. My D is the same which means my T has to be corrected. Sir, what decoder? My only distance decoder for what? What is that decoder? It will be the simple decoder, the ML decoder. Yeah. You don't want to go to the ML decoder for the long code. The ML decoder for the small code is not bad. The long code you don't want to do an ML decoder. That's the idea. I'm going to use the decoders for the component codes to decode a larger concatenated code. So that's the idea. What is the advantage that the component codes are easier to decode? The smaller block length is smaller. Maybe I have better decoders for them. I can implement the decoders and I can cleverly combine them to decode the original code overall. There might be some problems with error correcting capability and all that. But my decoder is very, very simple. Not only that, it can correct beyond error correcting capability. So the other boundary distance decoders are the problem that beyond error correcting capability there is a failure. These decoders won't have that failure. They will do something, eventually they might also decode. So there are both advantageous and disadvantageous. So those are important ideas. These kind of ideas are quite important. So there's another kind of concatenation which I'm going to talk about now. These are actually called concatenated codes. So that's kind of product codes. I'm not going to talk more about product codes. How will I write the generator matrix? You can do it. So you can think of it this way. If you have the messages, there are seven code words in the row. Then you have to first convert it into the error message. So it's a little bit more complicated. It's not that easy. It can be done. Maybe that will be a problem in the final exam. How do you write a generator matrix for the overall code? Parity check matrices also can be written. Yeah, here I search for a linear space. It's actually a length 49. When I say a length 49, 16 code, you write it as a 7 by 7 matrix. But it's a length 49 linear code. There's nothing wrong with that. How do you know individual basic vectors to get these separating? So parity check matrix I think is a little bit easier. You have seven of these things. Each of these things will usually satisfy the H. So you can put H in a block diagonal form. Is that enough? That's not enough. Then you also have the other columns satisfying. So another set of H will come in a slightly permeated form. So that's a valid parity check matrix. That fully gives you that. From there, you'll have to do elimination, go to a generator matrix. Maybe it's a little bit more complicated. Parity check matrix at least in principle is these. Yeah, I think it's possible to think about it. So essentially the overall code can be written as m1 times something plus m2 times something. So each method is multiplying some vector. You can do it. Maybe there's some chronicle product or something involved in the final answer. Might be eight commas. Think about it. So that's product codes. There are so many ideas there which are very useful. Once again, remember the idea, use two small codes to construct a bigger code. The big advantage is in the decoding side. You can decode with the two small codes to explore the local structure. You may not be able to observe any guarantees on error correcting capability but a large fraction of errors even beyond error correcting capability might be corrected. The next kind of concatenated code is a little bit more theoretical. I'll write it down here just for completeness. So in these ideas what we do is concatenated code. We also call form is concatenated codes. So you start with the one comma k code gf2 power m. So I'm putting all capital because small letters are also going to come. So gf2 power m. Let me be careful here. m comma k code over gf2 power, let me put small k. This is the first code c. Then I'll take an n comma k code but it won't work. Yeah, yeah, the two k's are the same. We have to be the same. Let me think about that once again. Let me make sure it goes fine. Yeah, I think it's fine. These two k's are the same. The same k here. I'm going to concatenate them using that. So what I'll do first is I'll take k times k bits. This is the overall message. And I take k times k bits. These are also k elements of gf2 power k. So I can encode it with c1. I will get n elements of gf2 power k. Or what? k times n bits. As n blocks of small k bits. Capital n blocks of small k bits. And then encode with c2 k at a time. What will I get outside? n times n bits. This is my idea. So I have an n comma k code over some field but I will not use that code like that. I'll use its expanded version. That's the idea. So when I use the expanded version everything is in terms of bits. So this overall code is called the concatenated case. So let me put some minimum distance here. Sorry for that. I'll add the minimum distance here. Perfectly deep. So my first question is is this code linear? So we're doing some gf2 power k conversion and all that. Is that okay? All that's okay. Because anyway addition in gf2 power k is the same as binary xor which is again addition in gf2. So this code is linear. There's no problem. What will be its dimension? It's going to be small k times capital k. What is going to be the block length, small n times capital n? What about the minimum distance? What can I say about the minimum distance? We don't know equal to which d. So think about it. Think about it a little bit more carefully. So you have n elements of gf2 power k. If I have a non-zero code word how many of those elements will be non-zero? dk. That's k in the picture. So I have a capital n, capital k, capital d code over gf2 power k. Every code where non-zero code word has at least how many non-zero elements? Capital d. That's the definition of minimum distance. Every non-zero code word of this code has at least capital d non-zero elements in it. So which means in my second encoding how many non-zero code words must be there? See in the second encoding what am I doing? I'm taking capital n elements and each element is being encoded into a code word in the vector representation. How many of these elements were non-zero? Capital d. So how many non-zero code words of c2 will I get after encoding? Capital d non-zero code words of c2 I will get after encoding. So each code word of c2, non-zero code word of c2 has what way? Small d. So what should be the minimum weight of the overall vector? Capital d times small d. Is that okay? So there's some argument here which you have to carefully think about. Is that okay? You're not convinced? Okay. So think about it this way. So I do. So I have here k times k bits. Each row is an element of what? gf2 power k. So I do the encoding here. What will I have? n times k bits each row is an element of gf2 power k. How many of these have to be non-zero? Some d of them have to be non-zero. Let's say these are d. What do I do in the next step? I take each row and encode it with c2. That's what I'm doing in the next step. Is that clear? Maybe what I'm doing in the next step was not clear to you. I take each row and then get the n bit code word of what? c2. So I have d non-zero messages to encode which means d of these rows will be non-zero and each row has to have weight greater than or equal to small d. So overall the weight will be greater than or equal to small d times capital d. If you view it in this matrix form it's a little bit clearer but usually you don't think of matrix when you're in this language. Just think of it as a rule. So once again we have a very similar idea where we've gotten two small codes and obtained a product like construction but this is not very simple product like construction. There is some complication here because we're going to this io field and you're doing some encoding there and then coming back to this binary field and doing some encoding there. So it's not very simple like product construction but nevertheless the principles that we had there are equally true. So there are two codes which are component codes of a bigger code. Then each code word has some local structure which you can try to exploit and do some decoding and try to conveniently combine it with something else. So let's take an example and see how this looks. Let's take I don't know I mean just let's take 255 what do you like so let's say 245.11 RS code word so just you can take anything else also if you like just taking this and then you concatenate with remember K is 8 so I need some code word K is 8 let's take the 9,8 even weight code 9,8 even weight code so 255 times 9 what is that 22 and what is this 245 times 8 24,0 divided by 8 is 2 are you sure 1880,1960 and then minimum distance is greater than 22 okay so if you just one read column and decode you can expect to only correct 10 errors,5 errors right this is saying minimum distance is 22 you should be able to correct 10 errors how do you put it together I mean is there any idea how will you correct 10 errors code word has this picture how can I hope to correct 10 errors suddenly it makes sense yeah that's true but I want a simple decode and I want to be able to combine these two decoders I don't want to say okay this is a overall binary code you do syndrome decoding on it is there anything that you can think of any smart ideas the 982 code what can you do you can't decode anything so that's the problem what can you do so what you do is for each thing there you find the parity if the parity is 0 you let it alone if the parity is 1 what do you do definitely there is an error so how can you help the reach element code you just say that's an erasure so now let's say there are 10 errors distributed over 10 different blocks one error each in different blocks then this scheme will correct why because I have marked 10 erasures and the reach element code can correct 10 erasures can I claim that this decoder the strategy that I am using all error vectors of weight less than or equal to 10 yes it needs more work I will have less number of erasures which means the erasures can definitely be correct once the erasures are corrected I will look at the code word I will look at the code word and that code word will not match it won't be a reach element code word so now I will have to correct the code word so be a little careful you can easily have an erasure plus error situation you have to do erasure plus error decoding and you have to be careful about that because if there are 2 errors in one block what will happen my parity will be satisfied and I won't mark it as an erasure but then if there are 2 errors there can be only 8 other errors and you have to worry about how many erasures I can have at this time I might have 8 erasures so if I have 8 erasures in one error I can correct the only thing is 2 times the number of errors plus number of erasures should be less than or equal to T so depending on the number of erasures you can keep adjusting my decode I know reach element is really easy correcting erasures if you select the polynomial is known and then you just do it is that clear so try to see if you can show that that strategy will work for any combination of errors less than or equal to 10 you can have a stage situation like 3 of 10 might be in one place suppose you have 3 errors in one block and then the rest of the 7 errors are distributing like erasures what will happen that is ok that works you might have some crazy situation is it possible can you always correct maybe it is possible so you have to think about it so it needs more careful analysis of the error events so what you basically have to look at is how do you get errors map on to block errors that is the crucial point if it is favourable to you then it is fine if it is not favourable it may not be fine so let me just leave it like that so you can do a decoder so basically you can do 2 decoders in the contact motion function you can mark erasures within a decoder if the inner decoder fails for instance the parity case it will really fail if the parity is not satisfied you cannot do anything so if you fail whenever the inner decoder fails you simply mark it as an erasure and the outer usually is going to be its element and you can help to correct errors like erasures and the tricky aspect is to show you what is the error correcting capability so computation of error correcting capability is a little hard but it is usually not so perfect it will work so error correcting capability will require a bit more work it is something you have to be very careful about even in the simple situation we saw that the combinatorics is a little bit involved you have to enumerate all the cases and see what happens I believe it is okay if you mark it as erasures you will be fine I think but you have to prove that okay so this is the concatenation idea I hope it is clear so we saw 2 different ideas one was the product construction which was a little bit simpler and the next is the concatenation idea which is also interesting okay we will stop with this today and this is kind of I mean I think maybe there is one or two more constructions that I want to talk about I mentioned that in the next class which will be next week Monday then after that we will move on to wait distributions and maybe close to it


Thank you, Lorna. We're on our way now. Katherine Cronin, you have information in your pack about Katherine and this information on the website and I imagine some of you already follow her on Twitter and in her many social media channels. She's from National University of Ireland. She's, this is a return to Scotland for her. She lived in Scotland for six years and it's a return for her to ALT. She was the keynote at the old conference two years ago and the delegates were inspired and enjoyed her presentation so much that we felt that we should try to attract her to Scotland to come and present at this conference. Her work focuses on online and open education, digital literacies and social media in education. She teaches and researches and she works with schools and community groups exploring open practice themes. She challenges us to think about openness in the context of equality and inclusivity. She has a degree in mechanical engineering, a master's in systems engineering and MA in women studies and her dissertation topics with gender and technology. She's a regular blogger and Twitter. You can follow along and her question to us today is, if open is the answer, what is the question? Katherine Thank you. Thank you. Thank you to all of you for the warm reception. Thanks particularly to Melissa and Lorna and the OER 16 team for inviting me here today. I'm delighted and honored to be here. It's not an exaggeration to say I think that in this room are a lot of the scholars that most inspire me and that I learned from and have learned from for quite a while. So as always I hope that what I bring this morning can just be part of the ongoing conversation of these two days and beyond and I'm really looking forward to what all of you are bringing it to the conference very much. I have to also thank this wonderful city that we're in Edinburgh. All hail Edinburgh. It's a beautiful morning. An amazing city. I didn't live in Edinburgh when I was here but I worked with the Open University when I was here some years ago. As many of you know an amazing city of art and architecture and science and technology and literature and because we have this very strong strand of open glam here today, our galleries, libraries, archives and museums, I just wanted to highlight two quick things that are inspiring to me. First is Mary Somerville, hands up who knows Mary Somerville. Eminent mathematician and scientist born in Scotland in 1780. She was widely honored in her day although you know I certainly never learned about her in school. I learned about her later in life and I'm taught about her. I just learned from Melissa recently that she will appear on Scotland's new 10 pound note in 2017 after winning a competition to who would be on that note. Please check out her Wikipedia page. One of the primary authors of that Wikipedia page is Melissa and I think I've made one or two contributions as well and her portrait, this portrait, hangs in the Scottish National Portrait Gallery on Queen Street. So if you have any time, if you haven't seen it before, it's quite something, particularly when you know a bit about her to see the actual portrait. And then the Scottish Poetry Library is even closer, it's in the Old Town and I've been following this Twitter account from the Scottish Poetry Library for probably seven years. I think it's the most wonderfully named Twitter account that I know by Leaves We Live. It's a line from Patrick Geddes who did pioneering work on city planning, a lot of that in Edinburgh. So a little bit of culture to start and two things that definitely inspire me. Someone said at breakfast this morning, how many times are we going to hear this word over the next two days? So I'll start, okay. We come from diverse areas and we have many different questions, but this is the concept that brings us together for these two days. And if you just pick up a dictionary of your choice, Google or Oxford or whatever you wish, there are so many definitions of the word open and we use it in many, many different ways. So it's from describing simple attributes to very complex changes and phenomena. So it has perhaps inevitably caused confusion and disagreement about what I mean by open and what you mean by open and what you mean by open. There's no orthodoxy here. I think that's the most important thing and critical debate is essential. So hopefully that's what we'll be doing here in these two days. The definition, which I hope might be a light for us for these two days, are these not concealing one's thoughts or feelings and not finally settled, still admitting of debate, being open to ideas, being open to change. So in that spirit of connecting and bridge building and because we're at the start of our two day program, I'm going to take a leaf out of Jonathan's book and I'm going to ask you to say hello to each other just to get that bridge building and connecting started.  Take a couple of minutes to say hello, ideally to someone that you don't know. And for those people who are participating virtually, please say hello online and hopefully people will respond. So please. Well, that was fun. Hopefully there's going to be a lot more of that over the next two days. And I'm sorry to cut it short. What I'd like to do now is the title of my my talk this morning is really open culture, open education and open questions, this whole notion of asking questions. So what I'd like to do is get to openness via talking about participatory culture. And some of you, anybody seen this mural before? Okay, few people here from Ireland and beyond. Just about exactly a year ago, this mural appeared at a very busy gable wall of a very busy street in Dublin, and it was created by an artist and activist named Joe Castlin, and was painted in support of the marriage equality referendum, which was held in May of last year and past May of last year. A three month campaign led up to the referendum. And this particular image became iconic and gathered much attention. I mean, it, it, it hopped back over into mainstream media, actually, appearing on the cover front page of the New York Times. And it, it, it was used in a number of different ways. So it was remixed by different people, different artists. This is an image created by Rebecca Hendon. And these images and messages were shared widely on social media as part of the campaign. These images and creations were not only in urban spaces, they were all created in, in rural spaces. This particular mural was painted on the side of a castle. It's not actually painted, it's actually created on paper attached to building with potato starch that can then just be washed off. So the drawings that are just exploded.  This was one that was near my home in rural Galway. But there was also guerrilla artwork that appeared in shop windows and street corners and empty walls around the place. And they were shared with various hashtags that were used as part of the referendum. So the main hashtag that was used over the course of three months was MARREF, the marriage referendum. And then people really use social media and very powerful ways to enter the debate even though they weren't in Ireland. So Irish citizens abroad in many different places began advocating for a yes vote saying I can't come home to vote, but I'm asking you to use your vote to vote yes. So in the weeks leading up to the referendum, Irish citizens intentionally created these very visual artifacts and shared them online with hashtags that they would hopefully have an impact on the results. And then final days before the referendum, use of the home to vote hashtag rose, which was incredibly powerful to watch. People tweeted, these were the people who were able to come home and place their votes. Irish citizens were left abroad, that activity on the home to vote hashtag peaked the night before and the morning of the referendum, people are treating again images and videos and so on. They weren't all serious. Although they were all wonderful. This one was widely shared and favorited and I do want to say that I had permission from all of the people who who tweeted these messages that I could use them in the presentation. I recroty an Irish journalist shared social media analytics like this one from the day of the vote. He was tracking the activity on different hashtags, vote yes vote no home to vote. This is the activity on the vote. Yes, hashtag from the middle of the afternoon of the vote. And this is kind of a larger view here. It's an incredible image, I think of the Irish diaspora. Looking at that activity. So I mean, I could have used any example of this is one that's particularly powerful and personal for me, but this wasn't a coherent narrative. This was, you know, it was not framed by anyone. It was through messages through photos, visualizations and artwork shared on social media using hashtags. A story was being told collectively. And it was a particularly powerful example of participatory culture, which I think is hugely significant in terms of openness. The participatory culture basically is groups collectively and individually having an impact or seeking to have an impact on culture. So this, of course, is just a single example. As I said, I could have used many others. It's probably atypical in the fact that it was focused on an particular event and a referendum and had a three month campaign, although certainly that was after years of activism. But there are many, many other examples. You know, right now, we are witnesses to a humanitarian crisis of enormous proportions with the refugee crisis. And I've spent a little bit of time recently exploring how open practices, open data and social media are being used. Not just in liking and sharing, but in where individuals and groups are getting together to try and affect positive change. So NGO, small companies, community organizations, collectors and so on. So participation is the driving force in social change. Henry Jenkins first defined participatory culture. And I'm a part of the foundation report in almost 10 years ago now, characterized by these five features. So participatory cultures characterized by low barriers to artistic expression and civic engagement, strong support for creating and sharing informal mentorship where people mentor one another and to create and share and so on, learn new tools. Members believe that their contributions matter. I think that's evident in the example that I just shared. And the whole notion of social connection is very important. We can also look at the literacy practices of participatory culture. And I again, I think this is really significant for us working in open education. So participatory culture is characterized by these literacy practices. Communication is multimodal, multimedia, networked, social, purposeful, often collaborative, or not always, and agentic. So this notion of agency is really important. So people choose their voice, the topic, they're not acting out of their role as students or teacher or librarian or whatever it might be, but from themselves in a civic sense often. Choose the genre and the tone, it might be humorous or serious. And the collapsing of space and time by the use of networked and open media is significant. So a question that I ask as an open educator is, hey, how successful are we in our educational institutions about developing and supporting these literacy practices? And secondly, how can we help every learner develop their voice and agency so they can contribute to the shared production of knowledge and culture? And I think that's a central question for many of us. So speaking as an educator, you know, one model that I've used in communicating this is this one. Teaching occurs, you know, generally in higher education in kind of three different spaces, physical spaces like this, bounded online spaces, like the LES and open online spaces. And there are good reasons for teaching to happen in all of those spaces. But if we limit ourselves to the first two spaces, there are many things that we cannot do. So we come together in education as networked individuals, networked teachers, networked students, and we meet. But if openness is not part of what we are doing, then we can't share what we're doing out with wider networks. But nor can we invite the participation of our networks into the dynamic learning spaces that we create. So and it's not simply a matter of going where the students are, like let's use Facebook because that's where students are. It's much more fundamental than that. It's about recognizing the ubiquity of knowledge and networks. But the imperative to facilitate not just learning but empowerment, civic participation and capacity building. So I think that brings us to openness, which is our theme. At present, that worked in open practices quite uneasily and unevenly within our higher education institutions, within formal education systems, full stop. Bonnie Stewart has a beautiful expression as part of her body of wonderful work in this area. Openness is a complex phenomenon. It's economic, it's political, it's technical, it's social. So how do we grasp it? How do we grasp the nettle and enable ourselves to be clear about our terms and our goals and engage in discussion with each other? So one way is to be clear about our interpretations of open, certainly. You could pick any number of levels and you can call them different things. This is just a model. Probably starting with open admission like the Open Universities, the whole network of global Open Universities where it's open admission. People don't have to have qualifications to enter. And then we get to open as free. So if you have the skills and the network access, we're able to access the open resources. And then we go beyond that again, and we get to OER, open the licensed resources, and then open educational practices or OEP. The yellow line is hotly contested and I'm sure there'll be many conversations about that. Open resources that are free, but that are not openly licensed, we may say that some of us may say those are not truly open. Well, according to the dictionary definition, they are open, but they're not our definition of open. So hence, some of the difficulties that we have. So OER, I'm just defining as licensed for the use. So it's OER embody the concept that knowledge is a public good. I'm saying take it, use it, remix it, share it as you wish. And open educational practices, a little more complex. I mean, I've been studying this as part of my own research. And there are really two bodies of definition. One is very OER focused or OER centric, which says open educational practices about producing, using and reusing OER. And then another set of definitions is emerging, that's much broader. So which says yes, it's about producing, using and reusing OER. But it's also about open pedagogies, open learning, open sharing of teaching and ideas and so on, about really changing the relationship with the teacher and the learner. This is not to say that many people who work in OER are not also talking about changing the relationship between the teacher and the learner. But opening educational practices is the definition that's being used to really talk about that. There's a two way arrow in my diagram between OER and OEP, because many people who work in OER make a great case for the fact that it leads to OEP. But other people show a more emergent use of OER, and I'm certainly finding this in my research at the moment, about educators who come to OEP because they want to democratize learning and use open practices with their students, and then find their way to open licensing. So these would be educators who don't work at institutions who have any policies around openness, for example. So in addition to our interpretations that we probably need to clarify when we're talking with each other, there are the different levels of openness. So individual activities, if you participate in a Wikipedia editathon, for example, or at CC licensing, going further you might have open practices. Many people who use open practices talk about their values as an open educator. They talk about openness as a way of being Jim Groom, because he describes openness as an ethos metal license. We did say that once, Jim. And a deeply held value, or even a political statement. However, the lower part of that blue box are really individual senses of openness. And really, if you have individuals spinning your wheels using open practices, but there's no commitment to openness at the institutional level, then it only goes so far. And I know a lot of people in this room are working precisely in that space. So I posed a question on my blog, a number of weeks ago, trying to try to invite people to who are working in this open space. So what, what's the question? And if you say, Yeah, I do open. So what's the question? What is it healthy to do? It's probably a kind of a different way of asking why. Lots of comments in the blog on Twitter, which was wonderful. And there was a webinar before this conference and they kind of clustered in a few different areas, some people really focused on resources accessing textbooks. Or as Lorna was saying, publicly funded resources on heritage and cultural sector. A large number of people talked about the whole practices, the importance of open practices and learning, developing, reflecting, connecting, collaborating, and so on. And specifically, empowering learners, the notion that we started with. And then there were a number of people who spoke about this notion of values, about how important openness is to them. As a practitioner, serving the democratic purpose of knowledge construction, and so on. And then a number of people just really got asked ontological questions like, you know, why isn't everything open and what is open and how do you define it? And let's be clear about our definitions. So that's a space. And if you were to draw a web network of just the few people that I've been corresponding with this about, you would find connections from all levels on each side intersecting with each other. And that's just a small group of open educators. Now that isn't people in the cultural heritage sector, or people involved in social activism, or anything else. So it's enormously complicated. A few months ago, Vivian Rolf and myself did a little bit of research before the ALT conference and assembled some of the resources that we found we were sharing regularly with people around OER and WIKI. And we created this WIKI educator. We didn't know that two months later, the US Department of Education would announce their go open project. But I campaign to encourage open licensing in the US. If you go and visit this WIKI, I'll invite you to look at the section on mapping methodologies, because we gathered together some really interesting work that's been done by different individuals to help them work with groups and institutions to kind of assess where they are with regard to openness and chart ways forward. So there's Daniel Ellers model, sharing the trajectory of OEP, Cheryl Hutchkins and Williams has eliminated the different attributions of openness. So we're moving beyond the binary of opening closed, which of course we must do. But even that, I think is not enough. And what's very important and so enthused to see as a important strand of this conference is openness as a critical and reflexive approach. So we know so much about the potential good of openness, and we're really good at communicating that. But there's a potential for openness to do just the opposite of what we intend to create inequalities. So students and staff who are already marginalized, structurally or otherwise can feel pressured to take on open scholarship and maybe disadvantaged by it. So it's not a binary open and closed, but neither is it a binary in terms of good or bad. And there's some wonderful work in this area. Richard Edwards, among others, in a wonderful article called Knowledge Infrastructures, I mean Scrutability of Openness talks about how openness is not, it's not a binary opposition. It's not a continuum, but we must always think about the context and think about what forms of openness worthwhile for whom. This is hard to see sometimes. And very hard to act or to address, rather, but having a critical reflexive approach is essential. Saba Singh, who's here today. Saba's presenting her work later on today at the conference, which is wonderful, talks about our privilege as open educators. This is really important for us to realize we may feel very comfortable in our networks that we have created for some time and really enthused about inviting our peers or students, but it's not the same. So every experience is individual and contextual. So we need to have that sensitivity in all of those interactions. We need critical research. I looked at the whole program and so I'm just going to name check a few people. I'm sorry if I leave anyone out, but again, so please see this strand on critical approach. Jeremy Knox, Vivian Roll, Suzanne Cosioglu, Sheila McNeil, Keith Sneth, Christian Friedrich, Leo Havenman, Javier Atanas, Andre Middleton, Katherine Jensen. Just a first look of the PAPA's program. All of these people are talking about critical approach to openness. I think this is wonderful and probably really the next stage of our work in this area. A small note. I'm almost finished about my research at the moment and I've been working with academic staff at one university that does not have a policy around openness to try and understand their use or not of open practices. And it's the key attribute that is important to people is this notion of balancing privacy and openness. So even in a small group of academic staff, people recounted instances of bullying or harassment or stalking either from a part of themselves or someone in their family. So no number of stories of openness are going to convince those people that it's a good thing to share. We need to be sensitive to that. Female staff, for example, are often marginalized in other ways and are very aware of the amount of online shaming and abuse that happens more frequently for women. So they might think twice again before putting it off and sharing. So openness entails negotiating new forms of risk, as opposed to the main point. Anyone can have a voice, so new kinds of boundaries and status hierarchies emerge. And just to finish up and in my study, I'm talking with academic staff, but I actually think this is relevant when we move beyond individuals and talk about institutions and that is it is always very personal. So we often stop at the macro level, say are you using Twitter, are you blogging, are you assigning open licenses, but the hard work happens beneath that, what I'd call the meso level and the micro level, so meso kind of a community. Who am I sharing with when I share in the micro level around personal identity? Who am I sharing as? And although people don't formulate the question as that, that's often where people trip up. It's not about the mechanics of retweeting and assigning a license. It's who am I when I express this voice in an open network. And one other level, which has come up in my study, and I'll call the nano level, is will I share this? Even when you've done all that work, you know, as somebody said, it's a lot of work to do for one tweet. You know when your fingers are hovering there and thinking of sending something out, you're negotiating these questions with every interaction. So we, if we're very experienced in openness, we might diminish that work, but it's very real. And so work around digital identity and context collapse is key for supporting people in this. And you know again, as someone in my study said, you're negotiating all the time. Every friend request, every interaction you're negotiating all the time. So work by the likes of JISC and in Ireland, the National Forum for Teaching and Learning, the work that they're doing around building digital capability, I think is very important. But we mustn't forget that we have to recognize privilege as many people, you know, Orby Waters, Dana Boyd, and so on have called to mind. So last slide, coming back to our word, open. And just a few summary. Openness is not universally experienced, so I don't think we can forget that. It's always complex and contextual. It requires digital capability and agency. It's both descriptive and aspirational, so we may choose closed conversations if our aspiration is open. Not everything that we do must be open, but if our aspiration is open, some of those mixed modes might get us there. And it leaves me aware of that. And critical discourse is essential. And just end with a quote from Trezy McMillan, we really need to move from access to equity and justice. And keep in mind our larger goals. And with that, I will just say thank you. And I hope to continue the conversation with you. So, get a few questions for Catherine. We're your friendly, but not very necessarily fast, Mike, bring us. So if you have a question, please raise your hand.  And we're also going to try and tweet some of the questions, so remote participants can read them. So if you have a question, please raise your hand. If you've left us features, Catherine. Yes, one over here. I'll come back to David. Catherine, that was an absolutely awesome keynote. Thank you. I just want to ask you about this relationship between learning and teaching. You made some, you alluded to the fact that the relationship is changing. I just wonder if you could expand a little bit more on that for us. Sorry, I'm from Open University. Thanks, Alison. Well, I mean, OER is it really points our way to that because it starts with the concept that knowledge can be co-constructed is indeed co-constructed. So, you know, the people who are involved with OER projects where you share, not only share knowledge that other people have created, but invite students to create and share their own work and CC license that changes the power dynamic. It doesn't eliminate the power dynamic of teacher and student, but it enables hopefully more equal sharing of knowledge creation. And I think that's that's where the most important thing. I think David can hand side. We're in the back. Okay, yes. Yes. Thank you for your talk. My name is Yoram. I'm from Germany. And I would like to ask you a question on the move from access to equity and justice question. I assume that's not only a question of where we have to move to, but where we are coming from. Many of us are coming from these questions. So, are we somewhat confused or lost between what we are coming from and where we have to move to? Can you say more? Ah, I hope you could. It's not only that most of us are not coming from the question of access, but we have a background in equity and justice questions. So, do you think we might have lost the focus on equity and justice on our way to open and too much focusing on questions on access and licensing questions and everything? Yes. Well, that's interesting. I mean, you're saying you're not focused on access, focused on equity and justice where I think many people who work in the area of open education particularly are really focused on access, you know, for very good reasons. But the point is that that's not enough. And that we have to think of, you know, access for whom and who's being excluded. And I think, you know, just what you said starting out with equity and justice will probably bring us to better open solutions than simply focusing on access. Hi, David Kernahan from the Followers of the Apocalypse blog and the internet. I firstly adjust the range and sheer awesomeness of the people that you're quoting from in your keynote. I just wanted to reflect for a second what a spectacularly rich field that is becoming. But I was interested that you didn't really talk about content in that still underpinning all of the benefits of open is the idea of open content, open educational resources, if you will. It's in the name of the conference. And over the last few years we seem to talk less and less about the content. I was just wondering if you could talk for a little while on what the place of content is in open. Do we need to be sharing content in order to be open or as open practice moved beyond content entirely? Yeah, great question. And it actually has been a strand of a lot of the conversation I've had even since I've arrived here. I deleted a slide from here because I was worried about timing just showing OER and OEP and arrows going to each. And I'm sorry if I appeared to minimize the importance of content. I suppose what I was trying to do was in a lot of our conversations we talk a great deal about content and it is important and it's a foundation for much of what we do. However, I was just trying to redress the balance of talking about the importance of process and equity and really a social justice vision of education. If we are just focused on the practices without the content that's not, I don't believe that is as sustainable. Is it? I mean because if we still have locked away content and we're having all these practices that's not in the interest of greater equity or greater social justice. So it's very much a dialectic I see between open educational resources and open educational practices but I would put them equally. I think what's happened is some of the work that's been done in OER has then come to practices about actualizing that great work that's been done in resources. However, what I'm seeing now is some people coming in to open practices from the social justice perspective finding their way to open resources. So I think we need to be able to have the conversations across that divide. Does that make sense? I just think the conversation is getting broader and I think that's a very good thing. Thank you very much for that. Rob Farrow from the Open University and OER Hub. Catherine, I think you're interested in something that I'm quite interested in which is something like what is the normative content of this openness commitment? And you want to say something like it's got a social justice dimension, it's got a critical dimension and you're kind of bringing these values to it, right? But at the same time, you're kind of sitting on the fence a bit about the definition side of things, right? So it's perfectly possible for someone to have a definition of open which involves none of these commitments at all. You might just think well it's just a practical thing that I do to share my work more widely or promote it or something like that. I think there is a way to get there and the way I'm trying to get there at the moment is through the idea of freedom. So for any open, OER, open data, open source software, whatever it might be, essentially when we talk about openness we're talking about removing some barrier to activity. So you can do something you couldn't do because it's now an open scenario. So I want to say something like it's always directed towards freedom, freedoms. Now if we go down that road we can have these thicker normative ideas because you can have an idea of freedom that involves not a commitment to social justice, respecting other people and so on and so forth. So I wonder if that's something that's occurred to you if you've kind of explored that at all or whether it's a kind of new perspective that might be worth exploring. Yes and I read your work about critical pedagogy and openness. I was very interested in that and hopefully we'll have time to have a conversation these two days. What I, in my own work, and again this is just my personal take on my approach to openness but I see connections with many people who are here. I think coming back to the question all the time of open for whom and under what conditions. For example, Laura Chernivitz has done some wonderful work around the values of the global north. So if we release and share open resources but don't allow them to be adapted and contextualized it's a very colonial approach to openness even though from our standpoint it may seem wholly valuable. So asking the question and it depends on what we're releasing, who we are, whether we're in the heritage and cultural context, whether in higher education. I think it depends on the context and releasing open resources is not a bad thing but it's often not enough and I also think again coming back to this notion of privilege. Those of us who are active in this space are quite privileged to have networks and supportive networks and agency to have these conversations and to share and to know that it will be received but if we encourage other people in more risky positions even within the academy to do that that can be quite dangerous for them. So I'm not criticizing open educational resources or openness but I'm just asking everyone to in their context ask the question who's being left out who may be at risk and I'm not the only one doing that work I think there's many people who are doing it but yeah new questions but important questions is that our time or how we're doing okay. Thank you Katherine that was awesome. I really appreciated it. The quote you end with the move from access to equity and if you go home brought this up as well or you're drawing my right with that brought this up as well as from the context and I really love that you're saying of the states this move from access to equity and justice building on what David said too so much of the infrastructure around OEOPS became a content and it became a political though undercutting the state funding of public education so the idea of openness and enclosure came hand in hand and so I was interested how would you all I know Europe is as complex as you know anything of think about this content relationship to textbooks and open like it's not a particularly American interpretation of open like you're also hearing your complexity without I'm coming calm text where we've almost boiled it down to textbooks which pisses me off so anyway that's I don't know if there's a question the answer is that is it less about text from here is is yes is a resounding yes although but many many people in this room have written about that and I mean I point to Vivian Roff has done a lot of work in this because Viv I think you've bridged the kind of two open education communities quite well so will you be talking about that in your session yeah but there there are definitely our cultural differences and isn't it wonderful that we you know some of us can can start making those connections and saying hey wait a minute it's not actually the same you know in this different area in this domain because that's really important you know because we do we do operate from within our frames don't we but it is different here here I say Europe I'm speaking from Ireland Catherine thank you very much for getting our conference off to an excellent start ladies and gentlemen round of applause for Catherine of course


Columbus Keith Short Senior. Yeah we on boss talk one on one, one on one. Yeah we gon' talk. Insanity. Insanity. Doing something over and over again expecting a different result. Exactly, cause I always tell people cause a lot of times I normally start out by getting your back story because you have a lot of people who come on here and they'll talk about how their daddy was, whether they were absent and you know I'm like okay, so how did you change that with your children? How did you try to break that because- That's real. I'm in the process. You know what I mean? I'm in the process. You know what I mean? Like I'm gonna keep it a buck because you know I found out, you know I'm from Kansas City, Missouri. I wanted to talk about that. Let's get into that. I wanna know- Hold on. Let's go back first before. Yeah that's what I wanna do. We don't know man. We wanna know- I'm from Kansas City, Missouri man. And you were raised how? I was raised- you jumped. So you just jumped a whole movie. There's a whole lot of stuff. Okay go ahead. I'll let you go. Go ahead. So coming from KKC, you know what I mean? My mom killed my dad or who I believe was my dad.  Columbus Keith Short Senior. Wow. He was a police officer in Kansas City. How old were you when that happened? I was two weeks from being born. Wow. Yeah. I was not born yet.  Like that third trimester when they came here and they- you know I was there. I was just in the womb. I was just protected. I've heard that. Do you know what I mean? So all of that. You know I heard the gunshot. I was there. I felt it. And you can be affected by it? Yeah yeah. That's why I like my whole life I didn't know. I was like man for a long time I got dem- I was like Batman. I didn't- I didn't wanna mess with no guns. You know what I'm saying?  I mean we working on it. You know- Do you have a relationship with her? Absolutely. Okay. When she gets real, when the gets real gets real, we can- I'm not ready to drop about the gets real. I'm gonna say this- Okay okay okay. People always you know they be like man you- because I go in. Like you say my- my- my- I could have been him.   And I was like three sitting there watching. Oh you watched it? Yeah. Yes I did. Yes I did. So when I say stuff like the people be like man you know the kids let them- But we going- I'm like we challenging the same energy man. I thought that he would have ran out but his dad didn't even run out. He ran after her. Yeah. I'm like she had a gun. He been shot in the head once. My daddy got shot. He did- This is country living.  And he ran up his own thing. No it never did penetrate. It stopped. And he put it in his pocket. He used to carry it around. You gotta be kidding me. I'm not playing bro. He used to carry it around in his pocket. I'm not playing. Damn. Different. And my uncle got shot in the same place. He got shot killed. He got shot in the back of the head. Ay man my mama towed up Kansas City.  She was bad. Jeanette Bentley towed Kansas City apart. And if anybody know Kansas City from 1982 she towed that motherfucker up. Wow. That's on God. And I can tell you know me I told my mama know that. I knew we cool. We can- Mom you towed it.  Are you the only child? I'm from Kansas City. Yeah. Yeah. Wow. So you were the only one who experienced all of that? I was- So my mom was going through the case. You gotta remember this. You know what I'm saying? You gotta think about that. Right. I was gonna be born in jail. So you know the shorts. The shorts. Edna's short. Richard's short. You know all the shorts. Janine's short. My auntie Nene. You know what I mean? They had to take me in. You know what I mean? They had to. Because that's who you know what I mean? Right. But it's crazy bro. But it's crazy bro. Because I just got my birth certificate like three weeks ago. And well I ordered it eight months ago. But I just saw it three weeks ago. How did it feel looking at it? There was no name on the- there was no father's name. Wow. So you know that's where the case began. But you know. Onwards and upwards. No the reason why I always like to go back into people because our viewers can see the elevation. See that it doesn't end with just you know something traumatic happening. No.  You have a choice to change your future. Correct. Not to live in hate. Not to live in anger. Not to live in what you did with. You know what I mean? You know what's amazing about what you're saying is what's empowering me is that I was talking to one of these, this young man who's like, he's like I don't know. Like a baby brother or like a son. But he was, he's went through a really bad situation. You know what I mean? He thought this girl, he was raising with his daughter. It wasn't his daughter. And it's like. A lot of people go through that. And he spiraled out and he you know overdosed and the other stuff. And you know we talked a couple days ago and I said man all you got to do man. Man it's not, I've been there. You know what I'm saying? Right. But you just keep pressing. You know what I'm saying? Do not quit. If you quit it's over with. Do not quit. That's the name of the game. Do not quit.  The reason why? Because you have the whole world watching you. That's what I'm saying. So whenever you, you know, people see you look a certain way or you know act a certain way. Right. They get to go to social media and oh he's going through this and he's this and that. If I had a phone back then when he cut up at the Palladium ballroom I would have, I would have put it out there. I would have been out here looking like a mystery back in the day. Cause they didn't have phones like that back then.  You cut up man. We're back in the day. Hey country. Hey, they didn't want us back in them days. No, no, no. It was ugly. We was burning down cities.


Hi, my name is Pratap Chatterjee and I'm the Executive Director of CorpWatch. I've traveled to the Middle East and to Central Asia more than a dozen times since September 11, 2001, spending more than 16 months on the ground in the region to investigate military contractors. I've visited Iraq four times and Afghanistan four times and traveled as a journalist mostly in the red zones, accompanied generally only by a fixer or a translator. In addition, I've also embedded with the US military and visited bases in Iraq, Kuwait, Kosovo and Afghanistan, and I've written two books on the subject, Halibutton's Army and Iraq Inc. The activities of the contractors are investigated range from low-skilled tasks like janitorial kitchen and transportation services to essential military logistical support functions like weapons maintenance and security protection. But by far and away, the biggest by revenue and employee numbers was Halibutton of Houston, Texas, who was once Dick Cheney and he quit that job just before he became Vice President of the United States under George Bush Jr. Halibutton's former subsidiary, Kellogg Brown & Root, often known as KBR, has grossed over $30 billion since it won a tenure contract in late 2001 to supply US troops in combat situations around the world. By the end of the 80 years of the Bush administration, the company claimed that its cooks had served more than 720 meals, its drivers had logged over 400 million miles on the road, and its workers had treated 12 billion gallons of potable water for the troops, or so they claimed. At the height of the war, there were 50,000 KBR employees or one KBR worker for every US soldier in Afghanistan and Iraq. The main function of these workers was to build and to maintain military bases, to make sure that soldiers were fed, their clothes were washed, and their showers and toilets kept clean. And while many stories have been written about the kind of salaries that some of these Halibutton employees make, $80,000, $100,000, and much more, in reality, most of the company's workers made a lot less, mainly because they were hired from countries like India and the Philippines, where a starting salary of $300 a month was considered a fortune. And it is actually very important to understand that these workers did not enjoy the same quality of life. And in fact, their lives were much harder than they expected when they left their countries thinking that they would make a fortune in the Middle East. To give you an example, I spent a lot of time with Fijian truck drivers who made hundreds of dangerous truck trips from Kuwait, in which they would drive large 18-wheel refrigeration trucks that carried all manner of goods, destined for US soldiers and bases in Iraq. But these truck drivers didn't get to sleep in the tents that they helped supply. They did not get to use those showers. They had to sleep in the trucks, and they were paid $2.50 an hour. While these employees were being exposed to mortal danger and they were underpaid, documents from the Army Corps of Engineers showed that KBR was charging the government double the market price for importing gasoline into Iraq from Kuwait. They also overcharged the US government for medial supply to troops at five military bases in Iraq and Kuwait. The company has also been charged with providing soldiers with unplurinated shower water and shard electrical work that caused a dozen soldiers to be electrocuted and killed. Take, for example, Staff Sergeant Christopher Lee Everett from Huntsville, Texas, who was killed in September 7, 2005 at Camp Takadem in Iraq, while he was power washing sand from the underside of a Humvee. On January 2, 2008, Staff Sergeant Ryan Masseth of Shayla Township in Pennsylvania was electrocuted to death while sharring his barracks at the Rathawaniya Palace complex in Iraq. You must understand that since 9-11, we've undergone eight years of invasions and occupations under Bush, followed by eight years of covert wars and assassinations under Obama. And today, we are less secure than ever before. And as we begin, perhaps the most uncertain and most dangerous period of US history since World War II, it behooves us to take a look back and figure out why and how we embarked on this path. The Middle East looks likely to explode in coming years, and the fall lies with us for lighting that powder keg. We don't need Nuremberg trial, but we at least need a South African-style truth and reconciliation commission in order to diffuse this anger, seek just solutions and move forward. And exposing the profiteering from this war is perhaps one of the most important tasks that we can undertake.


I think we've talked to you since the extension, so congratulations man, and what was your reaction to sign with us? First and foremost, I want to say thank you, it was good to see all you guys. Good to see everything worked out and happy to be back with some familiar faces. Now I'm just kidding, but man it's been awesome, it's been a blessing to be able to sign my third deal with the team and for another four years, so it's been amazing. Thank God, I think my family, I think my support system, I think my coaches and teammates, but the best fours are still yet to come and I'm excited to be here, stay home. What do we know what this team means to you? It means a lot, you know. When front office make a commitment to you and something that's earned, you know, and I'm looking back on the years that I've been here and I see different places every year and I've been consistent and it's been a blessing and doing something right. So I just want to keep growing, keep leading and just give my all. Was it kind of stressful at all when it was kind of hanging in the air and nothing had happened? I mean, we obviously don't know what's going on. Yeah, I mean, I wouldn't say it was a thing of stress, you know.  But, you know, if you wanted me to be here at home, you know, I still got some work to do and you know, I'm excited to get back to work with my teammates, my new teammates and new coaches, new staff. So I mean, it's been amazing to be able to be back. The energy is amazing and I'm just super, super encouraged for the season and I can't wait to get back to it. What would it mean to you if you could end your career here? It's very rare nowadays, but if you could be up and looking for life, DDP said you just certainly deserve life.  So I plan on playing for a long time, you know. So, I mean, if I'm going in the year 16, it might be like, look, man, we tired of having a run. I just, I just can't. But you know, you never know, you know, so I'm excited about these next, you know, four years and we're trying to make the most out of it. We got guys who are willing to compete, trying to go win a championship. And there's a lot of guys that came into this building, I believe in. And so I'm super, super excited. Brady, coach said that he felt like this group kind of had to chip on their shoulder. Would you feel like that this group feels like they need to prove that they can win anything? You know, absolutely, absolutely. You know, I feel like, and that's what makes it so exciting. You know, I'm a kind of guy that always had to chip on my shoulder so I can see it, you know. And so it's a lot of guys that's some great players that they're hungry. You know, they want their respect. And we want our respect as an organization. You know, Coach wanted to respect as a coach. You know, Terry wanted to respect as a GM.  You can't coach that and you go, it's only a field. I think everybody feel it, you know. And so I'm excited to be a part of a group like that. Everybody eat or learn. And so I mean, it's just a great, great time to be here. You talk about a lot of new faces. There's a lot this year. I mean, first time in your career, Matt Ryan hasn't been here. Yeah, yeah. Do you feel like you're kind of the face of the team now?  I think this whole organization, the Falcons, you know, it's a team. You know what I'm saying? About one player and about nobody. I've been here, obviously. But at the same time, we got other, we got other guys as stars, you know, what that's going to be up and coming. We got a great quarterback and Marcus Marriota. You know, we got a great draft pick and river. So you got guys to compete in this. It's going to be a team effort, you know.  All that stuff will play out. We let the media deal with that. You know what I'm saying? So it's all good. And we just, we just ready to grind. You get it. Thank you, Grady. Speaking of stuff, the media deals with everybody on the outside saying, you know, rebuilding things like that. Do you look at this team like that? Or how do you look at it? We prepare every day to win. We prepare every day to win. We ain't lying to take no over nobody. Man, a lot of things are going through my mind. Honestly, just like how the move was going to go. What to expect when I get here and a lot of things. But I'm excited about this opportunity, man. I feel like this is the perfect system for me to be in. And I really, really like just the people I'm around, the environment. And I feel like this is going to be a lot of fun for me. I feel like this is going to be a good place. Did you know a trade was coming? Did you have an indication? I did not. I did not know the trade was coming. It kind of caught me off guard.  So once I kind of, you know, grasped the idea that I was coming back to the right side of the country, I felt good. How much work did you do with Marcus and your time there? Quite a bit of work together. We kind of built up a working relationship. And I'm glad that he's the quarterback here because it's a familiar face, man. You know, anytime you're coming into a new NFL building, you know, it could be kind of hard to make that transition. So I'm so glad I have Marcus here just to make it easy on me. Some guy that I can pick his brain and ask questions to. There are lots of big guys in this pattern. How do you think that can help you guys? I feel like this system is built for big body receivers. We have a lot of those. And I feel like we can all just feed off each other, learn from each other and just grow as players. And I feel like we all can have a hand in this. Did you see Darren Waller's comments about you? I did. Darren Waller was a guy that I grew extremely close to.  So I really appreciate him and what he's done for me and how he's helped me grow as a player. Could you tell us a little bit about Conway? Oh, man. You know, not too much to tell, honestly. Small town, you know, very united community. You know, we all look out for each other. And, you know, I just have a lot of pride in coming from that place. And it kind of, it gave me my values that I still carry with me today. And I just have a lot of love for the place, honestly. You already mentioned how excited you are to come back. Can you just kind of elaborate a little bit more on that? Just tell me what has been back in the South. It just feels like home, man.  When you get in this profession, you really learn to appreciate the small things in life and I'm just so happy to be home. Hey, what's going on? How much did you know about Officer's Office before the trade? Did you have to go to YouTube immediately and start? I knew a little bit just from his past history in Tennessee. I did not get to watch a lot of it when he came here in Atlanta. But I just knew that, you know, he liked the big body receivers and they ran a lot of, you know, in-breaking routes with a lot of guys who can get the yak and make big plays off the yak. So, you know, when I heard I was coming here, I felt like it was a really good fit for me. It was probably as good as it was going to get. Any time a high-profile position player like a quarterback comes in filling in or replacing a guy who's been the guy for 13 years, there's a big spotlight from what you know about Marcus. How will he handle this? People tend to forget that, you know, Marcus is the highest trophy winner, man. So, he's not new to pressure, you know, and I feel like I remember a game back in Las Vegas.  And Marcus was like, hey, man, I've been here before. Cool, calm, collected, man. You ever talk to him, he says the gray hair is in his hair up for wisdom. So, I feel like if anybody can do that job, it's him, man. TJ H was talking about the value that he puts on receivers putting physicality. What about for you? How much pride do you take? I take a lot of pride in that.  Being in Las Vegas and, you know, these guys, they play physical here. The DBs are going to get up and pressure you. In this division, they're going to get up and it's going to be man and man. So, you know, I'm going to have a lot of fun just getting back to beating man and man, getting back to putting my hands on people and just being the true receiver I am. Yeah, absolutely. I mean, I always kind of view that relationship in the quarterback room kind of important and special. I always felt that a good quarterback room would really grow. So, you know, when we're out here competing, whether it's Dez, whether it's Felipe, we're all trying to make each other better. And at the end of the day, if they got questions or if I got questions, you know, they're a great set of eyes for me as well. So, at the end of the day, you know, we're all out here trying to compete. I think it just makes everybody a little bit better. I love it. I love it. You know, at every level of my career, I've kind of had to do it. And again, I think it's just a great opportunity so I look forward to it. I embrace it. And Dez has been awesome. He's a great young guy. And again, it's important that that room and those relationships be genuine. And I think it's been great so far. Who was your relationship with Bryan Edwards who later traded? Yeah, he's my guy. I love that guy. You know, we developed a relationship in Las Vegas. He came in as a rookie when I first got there. So we were kind of learning the system together. I love his competitiveness. I love his drive. I think he is a great addition to that room. Yeah, absolutely. It's nice to have a little bit of familiarity with the system. It's nice to come out here and just, you know, be around familiar faces. You know, I've kind of bounced around the last couple of years in my career. So to be around people that you know that respect and love the game is just as much as you do, it makes coming out here that much more enjoyable. Yeah, he's very hands-on. I think you'll see it. The system will have his fingerprint. But what's really cool about this staff is everyone gets to implement their ideas. You know, everyone gets to collaborate and create some just awesome stuff. So for us, as players, it's exciting. When you're sitting in install, you know, everyone's getting an opportunity to kind of learn the system together. And at the end of the day, when you get to come out here and do those things, it's a lot of fun. No, it's been awesome. You know, again, young guy coming in here, he's got all the physical ability. And I think for us, as we continue to help him grow, I think our entire quarterback room just has to continue to help him mature and learn the system so he can go out there and play fast. How much stuff has came back to you? How much, you know, the system is still the same and how much are you doing? There is some similarities, but there's also a little bit of differences which I think has to happen, right? I think over the course of a couple years, arts learn some things, has gone through different situations, different experiences. So I think being around it now, I like where the system's at. I think it really tailors to the people and the players that we have here. So it just allows guys to go out there and play fast and do their thing. How are you taking this opportunity different from those previous stops? Well, I think for me, personally, the last couple years was a learning opportunity. You know, for me here, previously, when I was at Tennessee, I had an opportunity to play. I was a starter. So being around that and then going and learning for a couple years, you're kind of hungry to get back on the field again. But my mentality and my approach has never changed. I've always tried to focus on getting better one day at a time, and at the end of the day, if things work out great, if not, I'll be a guy that's supportive and should be the best team player that I can be. Can you repeat the question, please? Yeah, first of all, I'm excited. With those guys in there, they make you look good. You don't always have to be perfect with your throws. Being able to have these guys, whether it's a catch radius, their ability to get in and out of cuts, these guys have really made all of us corebacks look good this offseason. It's a fun group to be around. A lot of energy, a lot of juice. I look forward to just continuing to get better with them. Can you mention how each of your stops is kind of this one more of that mentorship, leadership kind of role? I don't know. I think it's still pretty young to detail it that way. I really view it as another opportunity. I always kind of try to focus on what I can do to be the best player that I can be. But at the end of the day, we can all do good things to help this team. Mentorship? Yeah, absolutely. I think I've always felt that way no matter where I was in Tennessee or in Vegas. So, at the end of the day, I'm going to help all these young guys out. I'm going to do my best to be the best version of myself on the field. Just try to win games. Does it feel different to have so many young guys to work with? I think that's what's fun. You get to be a part of their and get to kind of help them shape what their professional career is going to be. I look forward to that. I think it's pretty cool to be a part of that, to have a little bit of influence. And we're just going to do our best to help them achieve their goals. Yeah, but I think really what we're focused on is just trying to get better one day at a time. I think the outside noise, what people say ultimately has no effect of what's going on in the field. I appreciate these guys. It's been a few weeks now. Just to come out here and just take care of what needs to be done out here and not worry about the outside noise. I think that's what motivates a lot of our guys. It's a cool group to be a part of. Are you looking forward to spirit? Yeah, absolutely. I've been in there a couple of times as an opponent. It'll be fun to be a part of the home team this time. I think a lot of it is experience. I think it's pretty impressive. Just his pattern recognition. He still physically can do it. Getting in and out of cuts. I've learned a lot from him. Just being around him. Being able to talk ball and be like, hey, what did you see there? How come you broke on that early? What can I do better? It's been cool because I've had that relationship with Casey for about a year now. I think he can also bring that to the young DB room. It's cool again. We had a good mix of older and newer players. What we can do to help shape these young guys is be a lot of fun.