Close elections force us to ask unpleasant questions about democracy. By Ryan McMakin, an audio-mesist wire narrated by Michael Stack. For months now, Democrats and other opponents of Donald Trump have been sounding ominous warnings that Trump may refuse to leave the White House even if he loses the election. This, however, has never been a remotely plausible scenario if Biden is the clear winner. In other words, if Biden wins a decisive or obvious victory, neither the Secret Service nor White House staff nor any government department will do anything to keep Trump in the White House. Rather, the only way there could be a meaningful dispute over who is the winning president is if the outcome itself is contested and unclear. In that case, a sizable portion of the population would insist Trump stay put in the White House while many others insist Biden was the real winner. Potentially, the result could be two full months of lawsuits, recounts and accusations of fraud before a winner, which wouldn't necessarily be Trump or Biden, is chosen. Even then, there's no guarantee that the general public would consider this to be a fair or legitimate outcome. Indeed, the longer a disputed election is up in the air and the more a correct outcome appears unattainable, the more likely a contested election is to undermine the perceived legitimacy of both the electoral system and the U.S. regime itself. There are at least two reasons for this. First, a contested election is likely to damage the political myths to which the public clings. When elections are contested and their outcomes dubious, more voters may conclude elections do not translate into a government guided by the will of the people after all. Second, contested elections illustrate that democratic contests have no theoretical or moral value for the problem of a tie vote. Moreover, since the U.S. regime has long tied its legitimacy, so closely to the notion of majority rule, elections that produce no clear majority become problematic. No matter the outcome, more Americans are likely to begin questioning whether national elections are rigged, unfair, or otherwise unreliable. Washington's technocrats, pundits, and politicians prefer an easy and effortless election during which no one raises any questions about the process or its outcomes. This facade of serene consensus so valued by the Washington elite was maintained virtually untouched throughout most of the 20th century, but then the 2000 election threw a sizable monkey wrench into the works. The naive view that every vote matters and that elections are decided by honest and diligent counting of votes ceased to be plausible to those who were paying attention. Even worse from Washington's perspective, the election wounded some key Washington institutions. Last year, former Supreme Court Justice John Paul Stevens recalled that the contested election of 2000 had been disastrous for the reputation of the U.S. Supreme Court. The court had long cultivated an image of being utterly detached from political contests. Once the court became involved in the election, however, and ruled in favor of the Bush campaign in Bush v Gore, it became far more difficult for the court to present itself as a non-political institution concerned only with public service. Quote, I remain of the view that the court has not fully recovered from the damage it inflicted on itself, end quote Stevens wrote. It is indeed likely that the court's ruling significantly ratcheted up the rank or over court appointments that has grown over the past 20 years and has diminished the public's view of the court overall. But the damage on the U.S. regime inflicted by a contested election would extend beyond the harm done to the precious reputations of Washington's technocrats like federal judges. A contested election would do harm to the democratic myths buttressing Washington's legitimacy with the general public. For instance, close and contested elections are always reminders that elections do nothing to reveal or demonstrate the will of the people. It is true, of course, that no election does this. The people have no collective will and no election serves to translate the voter's will into policy. But a contested election makes this all the more abundantly clear and difficult to deny. After all, if approximately half of the voters are against the winner, it is absurd for the winning side to claim, as it inevitably does, to have a mandate or that the winning side can exercise its power with any sort of moral authority. In the United States in recent decades, winners of presidential elections rarely manage to gain votes from more than 25% of eligible voters. No president since Reagan in 1984 has won more than 53% of the votes of those who actually do vote. Bill Clinton never won even 50% of the vote in either 1992 or 1996. The notion that these winning coalitions represent the will of the nation, of the voters, or of any other meaningful group of Americans has little basis in reality. Even among those who vote for the winner, the reasons for their vote are usually extremely diverse. Moreover, many elections, as was amply demonstrated by the 2000 presidential election, are, for all intents and purposes, tie votes. Even worse for the will of the people theory is the fact that democratic theory has never provided an answer to the problem of what to do when there is a tie. The tie vote of 2000 was effectively decided by a court decision. The tie vote of 1876 was decided by a commission of party officials. But in both cases, the outcomes were considered by many to be dubious even if short-term prudence dictated that dissenters accept the ultimate outcome as fate accompli. If there is a contested election in the U.S. in 2020, it will face the same problem. The outcomes will ultimately be based on the acts of king-makers behind the scenes. A contested election puts all of this into play and on display. When there is no clear electoral winner, the old platitudes about government of the people become less convincing. Government of which people? The half that wanted candidate A or the other half? The closer the vote, the more arbitrary the outcome is likely to appear. If it's healthy for the voters to see how ad hoc and haphazard, it all is. Indeed, for those who take a more realistic view of American elections, one might say there is a whole lot of upside to contested elections. Close and contested elections are usually the only time that it becomes nearly impossible to avoid asking difficult questions that the regime most certainly would rather no one ask. For more content like this, visit Mises.org.


Hi guys, with me Lisa, she is from University of Manitoba and she will tell you the details. Hi everybody, thanks for listening. My name is Lisa and I'm from the University of Manitoba in Winnipeg, Canada. Winnipeg is located right in the centre of Canada, about halfway from Toronto and halfway to Vancouver. We are a university that's really large and we have a very old history, we're from 1877. We're only 10 years younger than the country of Canada itself, so it's a very old university. We have 30,000 students and 6,000 are international from over 110 countries, so immense diversity, lots of opportunities. At the undergraduate level, which is what I represent today, we have over 100 programs and so there's really something for everybody and we're really proud of that. We certainly encourage you to explore that on our website, umanitoba.ca. The other thing I just wanted to mention is our student life. We have lots of things going on, everything from an Indian Student Association to dance clubs to photography. So you name it, you can do sports and activities and it's all there available for you outside of the classroom. Because we do know of course that those outside of the classroom things are very fun, good for your mental health and certainly round out your education. Finally, I think one of the big things to know about the University of Manitoba is that we are a very high ranked university. We're part of the U15 group of research institutions in Canada, which are your top 15 research universities. We're world ranked and certainly one of the things that makes us really attractive is that our price point in terms of our tuition is relatively affordable compared to other places in Canada. Finally, just if you are interested in immigrating to Canada, we have some great opportunities. It's a little bit easier in our province of Manitoba through the Manitoba Provincial Nominee Program. So that's definitely something you're going to want to check out as well. So thanks for listening and I hope you consider the University of Manitoba. Perfect. So Lisa, this is a very good informative session and thank you for this. If you are looking to connect with Lisa, let us know. We will gladly connect with you. Thank you. See you.


Today, I'm just going to work on working this horse in kind of a show situation, kind of grow him up a little bit, got a couple of these horses tied in this corners, or what would be the corners. And I'm going to do a lot of going with the cow today, I'm going to keep it real simple. It's going to work this horse until he's being real accurate, having some urgency about what he's doing.   Not going to worry about backing up a whole lot or shaping. Just going to make him get real urgent about what he's doing. He's being real good right there. Got a real stronghold of that cow.  This mare kind of almost wants to be a little bit too broke in the face. Sometimes she forgets to kind of move her feet. So I'm going to kind of ride her one handed here when I work her. I might just use this second hand just to kind of assist. But I'm going to kind of make her step her shoulders around and really move her feet and do it with a little bit of urgency. Just like on that other horse. Pretty much going to work this one the same way. I might make her move her feet around just a little bit more. Just while I'm on the cut here, just step her on around.  Hopefully do a little better job than I did right there.  Catch her there. Just want to get her almost a little stiff right there where she's moving her feet, not just her face. Because I know she'll bend and I know she'll grab ahold of that cow strong but I want her to move her feet when she does it where she's not a stride long like she was right there. Make her grab ahold of this cow here. I'm going to do it.


This is the OER team, I am Mahesh Sharma, my friend Shankul and my friend Nikhil. So basically the project, Development of Open Educational Resources Repository. So first thing first, let's get an idea of what is an OER. So it is a free access, these are the freely accessible and openly licensed documents. There can be any media resources, which can be useful for learning, teaching, like assessing or sometime for research purposes. They consist of some copy-left licenses, like that's a basic knowledge. Second thing, so on what thing we built our repository, alright. So on what we built our repository, we built our repository on dSpace and as most of us are not so familiar with dSpace, so first thing like what is dSpace? So dSpace is an open source repository, it's a Java-based application basically that allows us to capture, store, index, preserve and distribute our digital material. Basically it provides us the interfaces for administration, deposit, ingest, search and to access the tools, access the materials we provide them. Second thing like I'll try to explain what all we did in this project through the architecture of dSpace. So the architecture like it has the three basic layers, application layer, business logic layer and storage layer. In the application layer like it is basically so that we can communicate with the world outside the individual dSpace installed in a PC. So in the application layer, we worked on the statistics tools like we integrated our dSpace with ELK stack, after that we changed the web UI also and in the business logic layer, we worked on the search and the browse tools under the discovery implementation. We changed the authorization methods also, we provided some administration toolkit like in the profile page and the input page and we changed some E-Person group manager like stuff in which we changed the profile page and the input page fields. In the storage layer, basically we just integrated the JDBC plugin to integrate our database with LogStash, the PostgreSQL database with LogStash. Now structure of the dSpace, so this is like basically how the files are stored in our repository. In dSpace we have communities, a system can have zero to n communities and each community can have sub communities, this can also go to n levels. So basically a community can have sub communities and any community or sub community can have collections. So those collections only have items, an item can only belong to a collection and this item is only our resource, it can be the video link or the video itself or the PDF. So now coming to the implementations we made, first I'll start with the updating profile page. So basically by default the dSpace provides us with the dSpace profile page, contains the fields like name, contact number and some other fields like an optional password update field also. But as to make it look like more educational repository, we made a few changes and added these additional fields which were like which we used in our Kibana visualization later on. So approach for that is like we know that each user accessing the OER, for an each user accessing the OER we have an E-person object created in the back end of the system. So basically what we did is we had to update the schema for that E-person object and the following changes were made for this. Like we changed some XML and JSP files for creating new fields at the front end for fetching the data entered by users respectively. Some Java files were changed so to update the E-person object content. Some queries were made in the, additional queries were made in PostgreSQL database files to allow the storage of the newly updated fields. Second change we made was in the input page. Again by default the input page has some fields, some fields but and it uses the Dublin core metadata schema. So for adding our additional fields we had to make changes in the Dublin core metadata schema and for the same like, for the same we had to do the changes like first we updated the configuration files, the input forms configuration files and to make it reflect in the d-space itself we had to go in d-space and like only this administrator can make the changes in the Dublin core metadata schema there. So and apart from this we introduced some IEEE form and metadata fields too. Now my friend Shankul will conduct. So I have been discussing about the discovery module over here. So we know that this d-space, Mahesh have told us that it is a framework. So framework has multi functionalities been implemented, predefined. So this discovery module is also been predefined in the d-space module. So what is this? This d-space module have functionality provided for browsing for any of the resources for providing any of the, for browsing for any of the course module or domain. So it is also for face searching. What is this face is searching? We have gone to Amazon or something, Mintra like that. So we have searched out some clothes. So what we do? We search for some color, we search for some size. So that is basically this first searching. What is this? We categorize our search into different fields means whatever subject we want to search, whatever the contributor we want to search. This is being filters have been combined to provide us the best result into some query. So d-space, this discovery module has been implemented from the solar, which has been implemented the Apache Lucene framework. So this Apache Lucene framework uses the inverted index functionalities. What is this inverted index functionality? This is like, we have seen the, the index of our book. So we, in the book, what do we do? We not search for that word in the whole of the book. Like, we search for that word in the index and that we directly go there. Because for the first implementation, it is very hard to search for a word. So that is very much hard. So this is being, inverted index functionality has been implemented in the solar, which is then used by the discovery module. So what, the discovery module, we have implemented three things. First is the tagloud. What is tagloud? We have seen it multiple times in our lives. What is this? This is a visual representation in which each of the key word or subject has been, has been provided some weight, weight in the form of font, weight in the form of what is the color of this is, means any of the thing which has been used more or which has been accessed more should be provided more weightage. So that it would be like more of been attracted to the user which has been using that thing. So that is the tagloud we have implemented. Now second thing is, we have added some filters, means as Mahesh have told us, we have changed some metadata registry for that. We have implemented some other IEEE registry also. So for that, we have changed some filters and faces in the discovery module first, so that we are well defined with the community as well as any of the collection of home pages. And as well as we have implemented the recent submission module. So we want that if any of the course has been added to the repository, it has been, it should be shown into the home page. So what is this recent submission is, means if any of the courses had been added into the whole domain of the D-space, it will be shown into the home page of the D-space. As well as for each of the community pages, community pages, I am talking about the domains, means computer science domain or electrical domain. So in the electrical or computer science domain also, if any of the courses had been added, it will be separately shown for that community. This is the recent submission which we have implemented in the D-space. Now talking about the different thing, which is the OER dashboard. So D-space doesn't provide us some functionality about the dashboard for each of the user. In the modern world, we want that each user should have that thing that whatever the course you want to loan or want to have, should be separate with each of the user. That's why we have implemented each user's dashboard. So what is the functionalities methodology? First is the authorization. Basically, we want to authorize basically that user has the authorization to access his dashboard. If not, we'll be redirecting it to the login page. Secondly is the access. Access means providing access to means delete or to see that course or to add some course. So this is basically the OER dashboard. So I have told you the implementation. So what basically in the implementation is there means for adding any of the courses, we'll be using Hibernate means we have created some Pojo classes. These Pojo classes are being like get a set of functions for the user to see whatever the course you want to add it to is a dashboard. And then that is mapped to the D-OER class. Then D-OER class will be using Hibernate to just map it down to the post-grace SQL which we have using. And some programming in the GSP server for the request objects we have been seeing. Now in the like we have also implemented the means there are various resources in the OER like the video or the PDF. We want it to be displayed in the D-Space or in the R-OER only. Why? We don't want it to download each time we see or redirect it to the YouTube because in the metadata which we are having from the server, we have YouTube links and we want it to be displayed into the D-Space only. So that's why we have implemented video for video we have used video.js and YouTube.js as content-driven network server. So we have implemented that in a different server and we'll be using in our D-Space module. And for the PDF we are using iFrames and in those iFrames we'll be showing the PDFs in various courses or domains. And the additional modification we have done means D-Space doesn't have support for the MP4 videos so it has support for the MIME field so we have changed that and also we have slightly modified some UI on the D-Space to suit our OER repository which we want to develop. Okay so now we'll be talking about the ELK stack this will be talking about the locks and Nikhil will continue it. Now next we have ELK stack so what is ELK stack? ELK stack is the acronym for three open source projects, Elasticsearch, Lockstash and Kibana. So now moving straight forward to Elasticsearch. Elasticsearch is an open source full-text search engine which is document based and it uses JSON format to represent the data. Elasticsearch uses indexing for fast fetching of data. Now lockstash, lockstash is like a data pipeline that takes the unstructured data as input process data converts that unstructured data into structured form and later feeds that process data to other applications like Elasticsearch. The major three components of lockstash are inputs, filters, outputs. Next we have is Kibana. Kibana is a visualization tool which is used to represent the Elasticsearch data in the form of visual formats. The sum of the basic features of Kibana are its user-friendly interface, multiple customizable dashboards and real-time searching of index data. So why do we need Elasticsearch? Together all the different components of Elasticsearch provide a simple yet efficient solution for lock management and analytics. Lock management and analytics include collection of our lock data files, cleaning of the lock data, converting the unstructured lock data file to structured form, then analyzing our process data and obtaining the results. As you can see in this diagram, what we are doing, we have taken our lock file as input, containing the unstructured data. That unstructured data is passed to lockstash data pipeline. What lockstash will do, it will convert that unstructured data to structured form and will pass that structured data to Elasticsearch for further indexing. Once the indexing is done on the structured data, it is used by Kibana for visualization task. Requirement of a project was to create the visualization representing the information such as date, time, user login ID, IP address of user, accessing our repository. It also included information about the courses, domain and subjects visited by the user and number of times they were visited. The main task of our project was to read the lock files for that we have used a grog filter provided by lockstash. What grog filter does is it reads the lock file line by line and matches the each line with the pattern we are looking for. Once the match is found, the data is extracted and stored in structured form. For defining grog pattern, we have used regular expression. Once after reading the lock files, we got the data containing course ID, domain ID and subject ID. But to make Kibana visualization more precise, we needed their names also that were stored in the postgres database. So for that we have used JTBC driver which established a connection between our lockstash and postgres database to fetch the further information. Once we got that information stored in the database, we used the translate filter to create a mapping between our course ID, course name, domain ID, domain name and so on. After all this task was done, the whole data was passed in Elasticsearch where Elasticsearch did the indexing part and then Kibana fetched that data for visualization. Now I will call Shankul for demonstration. This is basically the d-space framework which we were talking about. So this is the recent submission tab which I have implemented. So like these are the six, the latest submission of the courses which have been implemented. We can just redirect it from clicking over here. You can see this is the tag cloud which I have talked about, means this programming language education. Basically in this tag cloud information, we are seeing that whatever the different subject is being used most of the time is talking about the frequency only. So this programming language education would have more frequency in all of the courses. So we can just click over here and it will redirect it to the whatever the courses this subject is talking about. So this is basically the tag cloud and this is the basically discovery portion we are talking about. We can see that there are different courses like we can go into the computer science course. I mean we can see that in the computer science course we have also recent submission. This is different from the home page. It will talk about only the recent submission for this computer science section domain only. We can see there are all those courses which have been implemented recently. We can see this is the course which has been implemented and we will go and we see this is the PDF and this is the iframe tag we will talk about. We can see that this PDF into the dspace only and this is the we can see the YouTube videos. This is the it is streaming live from the YouTube and we can see this and we can go on to any of the portions. So this is the basically the we were explaining and this is and this is basically the dashboard I was talking about. I have like in the earlier I was just implemented this basic electronics course into my dashboard and I can just redirect it to this course only from this dashboard only. So this was the basic demo and any questions. So thank you. Thank you.