You can search by last name, by zip code, you can sort by county (Pinellas, Hillsborough, etc.), by gender, height, weight, etc.  This is all publicly available information, but the way this website packages it is is something uniquely dehumanizing.

The first thing that surprised me is how many of the people look the same.  Similar hair cuts, similar expressions, and those people are often convicted of similar things.  Most of the people I picked out as “normal looking” were usually booked for DWI or possession of marijuana.  Most of the people I picked out as looking like “thugs” or “hooligans” tended to be assault, battery, theft, grand theft, etc.  I am surprised at how few Hispanic people are on the list — this is significant considering that Florida is a fairly Latino-heavy state.  Hillsborough County is 18% Hispanic, but they certainly seem to make up only about 10% of the mug shots using my unscientific estimate.

Also, the way the counties are ranked is slightly deceptive — clearly, Pinellas and Hillsborough are much more populous than Manatee and Pasco County, but the bar graph makes it appear that crime is several times worse in those counties, even when their crime rates are only slightly worse.

I suppose I shouldn’t be surprised at the fact that the plurality of offenders are 20–25 or so in age.

Here’s an example of someone that would frighten me:

Here’s someone who is named after an unreliable compact car from the early 80’s:

But that wasn’t Chevette’s first time in jail:

I don’t think traffic tickets are included on this page — if so, I would be scared, because I once forgot to pay a speeding ticket many years ago and would hate to think that I could potentially end up on a page like this.

I am no legal expert, but it seems like this kind of website should only feature those who have been proven guilty, at least for crimes below a certain level.  I would imagine that a small percentage of these people are in fact innocent, and knowing that their careers, their reputation, or their dignity might suffer as a result of this kind of website leaves me depressed and even more cynical about the justice system.

My interests:

beating stagflation, instilling rote rehearsal and efficiency from the checkout line to the breadline and the unemployment line, small businesses, startups that aren’t just another rehashed concept that will never be monetized, decentralized office structure, design driving data and not the other way around, consumer science, whistleblowing, whether it’s whistling while I work, during an extended break in a disco song, or whether it’s chewing the fat before the fat chews me, creative writing being merged into technical writing for the sake of simplicity, starching my ties because it might just help!, whipping inflation now! Reruns of Love, American Style, wondering how Goldie Hawn survived without laughing in too much, knowing how Sandra Bernhard spells her last name (with a ‘d’), chicken balti, trying to beat the baby boomers at their own game by not owning anything that would contribute to the tax base, wishing Dr. Jarvik had invented the artificial soul.

Groups and Associations:

Toastmaster’s Club of Brooklyn, Club Med, Club Soda, Club Crackers, Cluedo Clubdo of Basingstoke (my favorite), Club Tropicana (when Andrew Ridgeley is around).

Honors and Awards:

Top Scorer, Cash Cab, 2006
National Geography Bee, 1992
Naming that tune in one note, and hearing it above the gasps in the crowd
Toastmaster’s Award of Shaker Heights, with a Reduction of Expectorant followed up with Miss Pringle, a Yorkshire Terrier from Ripon.

Now, I have been accused of having a humorous vernacular that’s so obscure that nobody gets it, kind of like the “Shaka when the Walls Fell”  aliens (who spoke entirely in metaphor and therefore whose language was impossible to decode using the universal translator) from Star Trek: The Next Generation.  But surely something on here makes you laugh, right?  I am cracking myself up at the moment — still pleased that I’m able to be self-satisfied by my own humor.

Last.fm is one of the handful of RSS-enabled, social connectivity-type websites I consistently use.  (My user name is sophistidisco.) Ostensibly, the point of ‘scrobbling’ (from a business perspective) is to aggregate listening data in order to assess trends in popular music.   Then, there’s the actual jukebox part of the site, which I have to admit I never, ever use.   I have no doubt that there is a lot of value in using the data to upsell or advertise, especially to the music fan who is probably what you would consider an “intermediate fan” — someone who isn’t a music snob or music collector, but isn’t completely satiated by FM hit radio.  The problem with me is that every band they recommend to me (based on my scrobbles) is simply a band whose music I already know, and already know I don’t care for all that much.

A good example in my case is the band ABC.  Hell, I love “Poison Arrow” and even “The Look of Love”, if only for the latter’s bubbly pretentious-lite spoken ending: “And though my friends might ask me, they say, ‘Martin’, maybe one day you’ll find true love…” But I have listened to more than enough of ABC to know that they go from decent to cloying within 1 album, and I’m not interested in hearing a production value so clean that Stock, Aitken and Waterman sounds like no wave in comparison. But there is no way, as far as I can tell, for them to omit ABC and learn as to why I’m not interested.

The bottom line is that for the web 2.0 industry, I am the guy who pays my credit cards on time — i.e. I am not a profitable prospect because I know too much.  I just love the free stats:

My top 10 albums of the past 2 years:

1. The Associates — Fourth Drawer Down
2. The Associates – The Affectionate Punch
3. John Foxx — Metamatic
4. OMD — Orchestral Maneouvres in the Dark
5. The Associates — Sulk
6. Alaska y Los Pegamoides – Símplemente Lo Mejor
7. Pete Shelley – Homosapien
8. ABBA – The Complete Studio Recordings
9. Ultravox – Systems Of Romance
10. Japan – Tin Drum

I want to start extracting last.fm and putting it on a spreadsheet, so I can discern more telling information, such as year of release and country of origin.  Also, I want to find a way to show song density for each artist.   For example, my #2 artist, Simple Minds, is largely #2 because I left it on “Simple Minds” on iTunes one evening, and I happen to have their entire back catalog.  In reality, I only listen to their first four or five albums and almost never listen to anything beyond 1985.  So the song density should be low.

Simple Minds: 308 scrobbles, 118 songs.  So that number is clearly arrived based on the fact that I have a large amount of songs in my overall library to begin with.  Density (i.e. scrobble/song) is 2.6.

But what about the many artists I listen to that never released LP’s and were brief in their output?  The brilliant and almost entirely unknown new wave singer Greg Vandike released only a handful of 7″‘s, and I love them all.  I’ve played his songs 46 times, but only from 4 singles.  Density: 11.5

One of these days, I’m going to find a way to scrape the data from my own “lifestreams” and compile a bunch of analytics on my own life.  It sounds pretty god damned lame, but look who’s talking (or blogging!)

And then there’s just the feeling of simultaneously being isolated and feeling smug when you find out that you are the “top listener” to a certain song or band.

Their rankings metrics are totally messed up, though, although some do seem plausible. Of the million plus last.fm members, apparently I’m the #2 listener of the Associates, which itself has 260,000+ listens. The data for who is actually the top listener of a certain song appears to be based on criteria that I’m unaware of — I am not the top listener of the song “Darling Don’t Leave Me” by Robert Goerl, yet when I click on the ‘top listeners’ and find that song in their library, they didn’t listen to it nearly as much. The song “You Keep Me Hanging On” by Bernie Nolan and B.E.F. (a remake obviously) is not even in the library of the top listener’s scrobbled songs. I’ve listened to it 15 times! He (nice guy I am sure) has listened to the entire band only once.

If you dig deeper into the statistics of the song itself, it has been listened to 19 times in the past 6 months. When you dig deeper into my statistics, I have listened to it 10 times in the past 6 months. Doesn’t that automatically make me the top listener? How is it statistically possible otherwise? Seems like an error.

Either way, this datacatessen is out of pastrami. I’ll bore you with my nicoise number salad another time; let’s listen to one of the least known covers of one of the best known pop songs of the last 40 years:

• Bernie Nolan with B.E.F. — You Keep Me Hangin’ On