Review: Girls

A stretch of sick days, coinciding with my having finally gotten HBO GO running on my iPad, found me watching the first season of “Girls”. The show was created by and stars Lena Dunham, who has been criticized online for everything from not being progressive enough to not being thin enough. Having heard zero about the actual content of the show, I looked it up in the HBO app and pressed play.

I have to say, I hadn’t expected to like it as much as I do. Not to say it’s without problems, but I enjoyed it and will likely catch up with season two.

The premise is simple; four young women in New York are struggling with the transition into adulthood. Dunham’s character, Hannah, has just been financially cut off by her parents. Nothing out of the ordinary. In fact, as has been pointed out extensively, we’ve seen plenty of privileged white youth supposedly struggling in the big city.

While I join the chorus of voices pleading for more diversity, this isn’t the show to complain about. Not that it isn’t absurdly pale for a show set in a major metropolitan area. The show can and should do better at reflecting the richness and variety of culture that surrounds its main characters. I just don’t think it’s a valid example of business-as-usual television.

Although most episodes of the 10 episode season are half an hour in length, it is not a sit-com. It’s often funny, but there are no catch-phrases, the situations change, and everything doesn’t get resolved. In a sit-com the discovery of a diary leads to hurt feelings, misunderstandings, and finally heartfelt apologies. In “Girls” relationships are strained and destroyed. It’s a subversion of story cliché of the sort that the show tends to do well.

There are exceptions. Shoshanna (played by Zosia Mamet) is treated poorly in this season. She is the least defined of the four friends, and she tends to surface only to serve as butt of jokes. In her longest appearance, she manages to accidentally smoke crack and leads her guardian on a chase through oddly empty streets. This is a time where the show descends back into formulas, and while amusing moments like this feel like a let-down.

The movie “Pleasantville” deconstructed the world of mid-century sit-coms by allowing disruptive change. This kind of change can introduce advancements while at the same time undermining business models or established ways. In one memorable scene the family patriarch returns to an empty house. No one is there to greet him or ask about his day. Suddenly his world has been overturned, his privilege stripped away, and not everything about him any longer. There is nothing he can do but wander through the dark rooms asking the emptiness where his dinner is.

At it’s best “Girls” reminds me of that moment, where someone who doesn’t even understand his or her own privilege is confronted by its absence. These characters have had the rug pulled out from under them, and they have to decide whether to regain their balance or behave as though they never lost it. It remains to be seen which way they’ll go.

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Review: Brick and Mortar Book Recommendation

I told you about that book I got at Aunt Agatha’s. You know, the one that Jamie recommended when I went in to sell a book. It was A Cold Day in Paradise by Steve Hamilton. I’ve got an embarrassing amount of unread books, so at the time I put it on a nearby stack with a mental note to get to it soon. Since I had mentioned it in a blog entry, I thought I’d like to read it fairly soon and follow up with a review.

Not of the book — a review of the Jamie recommendation system.

Now that I’ve finally had the chance to read it, I am happy to report that the recommendation did well in all categories. Let’s break it down.

Customer data

Here’s what Jamie knew. I’d come in to sell back a mystery novel that I hadn’t liked. It had grabbed my attention with its setting in Michigan’s Upper Peninsula. My stated objections centered on the lack of action and of general threat.

Additionally, he knew that I am a big fan of the Hard Case Crime line of new and reprinted noir. These include works by authors like Donald Westlake, Lester Dent, and Mickey Spillane. They tend to be violent, pile up the corpses, and involve a bit of enthusiastic back stabbing.

Alignment of book content

The first correlation of the book’s content to known user data is that the action of A Cold Day in Paradise centers in the Upper Peninsula. Specifically, the murders happen in and near Sault St. Marie, and the protagonist lives just a short drive away. Since the setting was what had attracted me to the book I’d returned, this is a strongly relevant component of the recommendation.

As for addressing my objections to the other book, Hamilton’s novel has a gun fight, a couple of brawls, a murderous stalker, and an extremely suspicious sheriff. This certainly addresses my desire for more action and danger. Here again the recommendation scores well.

Moreover, the book has a great pulp feel to it. The hero is fallible, a cop who retired because he froze and carries a bullet near his chest like a badge of shame. He’s afraid of guns and still has nightmares about the incident that ended his career and his partner’s life.

As a reader I wanted him to succeed, to conquer his fear and start living again. This is important to me. A plot is a series of events, but a character interacts with those events and struggles to gain even the smallest bit of control over them. That’s a story, and that’s what I’d returned the other book for lacking.

Conclusion

Jamie took my statements about the book I’d sold back, mixed them with knowledge of my purchase history, and made an accurate and effective recommendation of a book I would like.

“Well,” a convenient paper tiger may reply. “So what? Amazon does as much.”

Here is the difference.

While Amazon knows my book purchase history (and my item ratings, if I used that feature) it doesn’t know why I’ve bought them. Was it the writer? Genre? Appearance of a big damn spider? The word zombie in the title? When Amazon recommends something to me it’s based on algorithms comparing my recent purchases with the purchase histories of other users, playing the odds that people who buy enough similar items will have the same general taste.

It’s a good attempt, and honestly I find a lot of cool stuff based on these recs, but the price is having to sift through a lot of things that I don’t want at all. Sometimes it takes a few pages of recommendations to find something in which I’m vaguely interested.

Jamie got it in one try. I recommend his recommendations.