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How To Contact Elected Officials

by Heidi Lauritzen on February 9th, 2017

Want to make your views known to the elected officials who represent you?  Here are quick links to the contact information for the elected officials who serve Johnson County residents.  Officials at the federal, state, and county levels are included, as well as city council members in Iowa City, mayors of other towns in Johnson County, and Board members of the Iowa City Community School District.  Click on the level of government you are interested in, and you will find names, addresses, phone numbers, and when available, the official’s website address and contact form.

Not sure which state or federal official represents you?  The Iowa Legislature has an easy-to-use “Find Your Legislator” feature for anywhere in Iowa.  Search by your own street address, by city name or by zip code.  For school officials, you can search by your school district.  It looks like this:
find-your-legislator

 

 

When you search by your street address, your Iowa representative and senator will be shown, with a chance to request info about “Other Elected Officials”.  One more click, and you will see your two U.S. senators and your U.S. representative, all with links to their websites where you will find contact information for letters, phone calls or email messages.

The Johnson County Auditor’s website also has a directory of elected officials.  Their directory includes some of the lesser known levels of local government, such as township officials,  members of the Agricultural Extension Council and the Soil and Water Conservation District, and all the school districts that are situated wholly or in part in Johnson County.

Evaluating News Sources

by Maeve Clark on February 7th, 2017

Fake news. Alternative facts.  The post-truth world.   In this rapid-fire world of social media, how do yohow-to-spot-fake-newsu know which sources to trust and which to dismiss?  First of all, ask us. Librarians have been teaching information literacy for as long as there have been libraries.  The International Federation of Library Associations infographic and blog post can help you make educated decisions in evaluating news sources, (and Internet sites in general). Be wary of clickbait, those eye-catching and provocative headlines can lure you in but what you find when you click may be of no substance at all.  If you aren’t familiar with an author, do a search.  What else has he or she written and which publications or online sites publish his or her work? Another clue the credibility of a source is the date.  And older article can, of course, be relevant, but can also be misleading.   And don’t forget to check your bias.

On the Media, a WNYC program which airs on Iowa Public Radio, offers guidance on assessing the credibility of a source onthemedialn-blog480of fast breaking news.  Anonymous sources are a red flag.   If something doesn’t ring true, trust your instincts and find another credible source or two to confirm the original story or prove it wrong.    The American Press Institute lists six questions to ask yourself when determining whether or not what you are reading is trustworthy.    They suggest you evaluate what type of content you are reading.  Is it an advertisement or opinion piece or is it a rigorously researched investigative article.  Look for what sources are cited to buttress the piece – are they credible?  Does the article or post tell the whole story or do find yourself  asking what is missing.

If you want to read more about how Americans consume news, the Pew Research on Journalism and Media has been studying how media is consumed for years.  The results of their most recent surveys are sobering.  If you have questions about a news source,  ask a librarian.  We are ready to help you.

Hurry up spring!

by Maeve Clark on January 25th, 2017

sunshineHave you missed the sun?  It’s out there, of course, though hiding behind the clouds that make our days seem so grey and dreary.  Is January the greyest month of the year or are we simply experiencing a run of gloomy skies?  It turns out that November or December are the least sunny months, with January and February giving the last two months of the year a run for their money. When trying to find easy to understand reports and statistics I stumbled across Brian B’s Climate Blog. Brian Brettschneider, an Anchorage-based environmental planner and climatoldrearinessogist, has analyzed a myriad of weather and climate statistics and created a Dreariness Index map.  He uses three variables to create the Dreariness Index – total annual precipitation, days per year with measurable precipitation and annual cloud coverage.  Iowa falls smack dab in the middle of the range, which if you are like me, knowing that we aren’t the dreariest location in the United States helps, at least a little.

If you would like to learn more about weather, the library has a good number of books on the subject, ranging from weather prediction to extreme weather to climate change.

Inauguration history

by Melody Dworak on January 20th, 2017

inauguration-quarrelWhen major historical events happen before our eyes, it can be fun to turn to the wayback machine and explore what it was like in the past. Thanks to the Historical New York Times database, I can take this trip down the collective memory lane. Read the rest of this entry »

Creating a List in the Catalog

by Anne Mangano on January 17th, 2017

The My List option allows you to create a list of items (books, DVDs, CDs, anything in the catalog) that you can reference later. I use it to keep track of books I would like to read at some point, especially since I always max out my holds. You can create multiple lists, so if you want to create a list of mysteries or travel books or holiday cookbooks, you can create a list for each topic.

Adding an Item to a List/Creating a New List

When you found what you want to add to a list, under additional actions, click on the icon of the shopping basket.

Read the rest of this entry »

Celebrating Martin Luther King Jr. Day

by Jennifer Eilers on January 10th, 2017

marting-luther-king Today at the information desk, we had a patron looking for Martin Luther King Jr.’s  “Letter from a Birmingham Jail.” The patron wanted a printed copy to read in order to celebrate MLK day which is this coming Monday. While looking for this letter online, we came across Stanford University’s collection of King’s papers which have been digitized. We found a digitized version of an early draft of the letter along with a recording of King reading the letter. You can see other items like King’s birth certificate, an invitation to the inauguration of John F. Kennedy, and much more on the site.

Read the rest of this entry »

Where do emoji come from?

by Maeve Clark on December 28th, 2016

foodemojiI have recently read a couple of posts about food emoji and really wanted to learn about how an emoji goes from an idea to a pictograph on my phone and why there are only 82 food emoji. The Unicode Consortium Emoji Subcommittee makes decisions about adding new emoji. Unicode is a computing industry standard for the consistent encoding, representation, and handling of text expressed in most of the world’s writing systems.  The standard is maintained by the Unicode Consortium.  The first emoji were created in 1999 in Japan for cellphone users.  It was a way to express something in a single character when text messages were limited to 60 to 140 characters.  Emoticons, not be to be confused with emoji, first appeared in 1982.   iemoji.com  is a great site to learn more about the world of emoji.

The more I read about Unicode and the consortium, the more confused I became.  I felt like I was reading a foreign language written in English.  But I did find out how you can submit a proposal for a new emoji. Not all submissions are approved, here’s a tumblr of emoji rejected by the Emoji Subcommittee. If you are curious about how an emoji is expressed across platforms and social media sites take a look at emojopedia.org.

Brave the snow knowing where to go

by Anne Mangano on December 16th, 2016

This weekend, meteorologists predict we’ll see one to three inches of snow followed by temperatures only inhabitants of the Yukon territory should experience. With a forecast such as this, you need to know the best routes so you can complete all of your weekend responsibilities, whether you are working or getting all of your errands out of the way. And it doesn’t help that we seem to be getting snow every weekend! You do not want to get stuck, not when the warmest socks and the warmest boots will not do. So what roads are your best bet?

Read the rest of this entry »

A holiday for everyone

by Candice Smith on December 9th, 2016
A holiday for everyone Cover Image

I grew up with a Christmas experience that I think will be familiar to many in one way or another. I was raised Catholic, so for the first 18 years of my life I did attend mass; this was usually on Christmas Eve, and it was very exciting to me as a child because the church lights would be turned off as the priest walked down the aisle, swinging a thurible filled with smoky incense. It seemed very exotic, not the regular day at church. We would hear the story of the birth of Christ and the three wise men, sing songs, and depending on which mass we were at, there would be a children’s pageant. After, we would go home and have a meal together, and my sister and I would head to bed while my parents stayed up a little longer. In the morning, we would be led from our rooms to the kitchen, eyes covered so that we couldn’t peek at the presents under the tree. Only after breakfast were we allowed to go open the presents; one person was designated to pass out the gifts, and they were opened one at a time. In this way, a good hour or two was spent opening presents and watching others do the same, eventually covering our living room floor with colored paper. Read the rest of this entry »

The Reverend vs Spam

by Todd Brown on November 29th, 2016

Thanks to the Reverend Thomas Bayes your inbox is not full of spam.

What does spam have to do with a Presbyterian minister who died in 1761? He was also a statistician and formulated a theorem which bears his name, Bayes’ Theorem. Basically it allows us to adjust the probability of an event given new information that might be related to the event. We can change the probability of an email being spam after getting more information by looking at the contents of the email.

Without Bayes’ Theorem we could look at our inbox and see that on an average day we get a certain amount of spam. The probability that any given email is spam would be the number of spam emails divided by the total number of emails. For example if I received 100 emails today and 70 of them were spam then the chance that any random email would be spam is 70/100 = 70%. But without any more information we still would not be able to predict that any given email was more likely spam than the others. The probability is the same for all of them so not helpful.

But what if we have some new information? What if we know that spam emails often have the word FREE in them? Bayesian Spam Filtering will look through the text in each email, if it finds the word FREE then using Bayes’ Theorem the probability of that being a spam email increases. Spam filters are all a little bit different and look at a variety of things to help them make predictions. Most will have a large list of words, with different weighting, that it looks for. Other things might be if the email has a lot of html tags, the image to text ratio is high, or the subject is in ALL CAPS. The filter is also constantly learning and adjusting the weights by looking at what users have marked as spam. In the end it gives each email a probability and if it is above the threshold set in that filter, then it is automatically marked as spam, put in your spam folder and you do not have to deal with it.

Thanks Reverend!

If you are interested in two slightly more detailed examples of Bayes’ Theorem keep reading.

WARNING: MATH BELOW
vvvvvvvvvvvvvvvvvvvvvvvvv

The basic equation is:

           P(B|A) * P(A)
P(A|B) = ----------------
                P(B)

P(A) and P(B) are the probabilities of A and B by themselves.
P(B|A) is the probability of B if we know A.
P(A|B) is the probability of A if we know B, which is what we are trying to determine.

An intuitive example is if you pull a card from a deck of cards what is the probability that it is a King? We know there are 4 Kings in a deck of 52 cards, so the probability that we drew a King, P(King), is 4/52 or 1/13. Now what if we had some new information about the card? What if we knew that the card we drew was a face card? Now we can use Bayes’ Theorem.

                 P(Face|King) * P(King)
P(King|Face) = -------------------------
                        P(Face)

We already know that P(King) = 1/13. There are 12 face cards in a deck of 52 cards, which means that P(Face) = 12/52 or 3/13. The last part is P(Face|King). We know that if we drew a King then it is definitely a Face card, so P(Face|King) = 1. Plugging these parts into Bayes’ Theorem gives us:

                 1 * 1/13
P(King|Face) = ------------- = 1/13 * 13/3 = 1/3
                   3/13

Having the extra information about the card changes the probability that it is a King.

A counterintuitive example is testing for a disease. If we know that 1% of people have a disease. The test for the disease is 90% accurate. If you have the test done and it comes back positive what is your chance of having the disease? The intuitive, but wrong, answer is that you have an 90% chance of having the disease. Let’s use Bayes’ Theorem again.

                           P(Positive Test|Disease) * P(Disease)
P(Disease|Positive Test) = --------------------------------------
                                     P(Positive Test)

The tricky part on this one is the P(Positive Test). Of the 1% of people who have the disease it will correctly give a positive result 90% of the time. But, of the 99% who do not have the disease it will incorrectly give a positive result 10% of the time. The resulting formula is:

                                  .9 * .01
P(Disease|PositiveTest) = ------------------------- = 8.33%
                           (.9 * .01) + (.1 * .99)

That means that instead of a 90% chance of having the disease, you really only have an 8.33% chance of having it. In this case knowing the accuracy of the test makes a very big difference in how the test results should be interpreted.




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