kaberett: Photo of a pile of old leather-bound books. (books)
1. I assume I have gone on at all of you who might be interested about how the PACE trial finding that Graded Exercise Therapy and CBT "cures" CFS/ME is a crock of shit? Just in case, it's a crock of shit, if it's not working for you the problem isn't you.

2. STATS QUESTION (because the last time I actually had to do any to pass an exam was circa summer 2008 and I have been resolutely ignoring the majority of it ever since): I have two datasets, one much larger than the other. For one (~2500 data points), the concentration ratio A/B is very uniform, makes a nice flat line when you plot it against B, *and also* This Other Quantity B' is also pretty uniform. For the second (~75 data points), the concentration ratio A/B varies over several orders of magnitudes, makes a nice *sloping* line when plotted against B, and there's also a lot of variation in B' (again, a few orders of magnitude). Is there... any useful way for me to say, in a scholarly fashion, "look, when A/B is uniform so is B', but when A/B isn't uniform B' isn't either", or...? (A/B doesn't have any straightforward correlation with B', it's the *range of variation* in both that I think might be correlated.)
kaberett: Photo of a pile of old leather-bound books. (books)
There is a standard ("Aldrich") that I measure ~10 times per mass spectrometry session, to make sure I'm getting approximately the right numbers out. I currently have ~104 measurements of this standard, with a standard deviation of +- 0.45 units.

I also measure samples, with number of (acceptable) measurements per sample between 2 and 13 inclusive.

Where the standard deviation between measurements for a sample is greater than my long-term stdev for the Aldrich, I use the standard deviation between measurements for the sample.

Where the standard deviation between measurements for a sample is less than that for Aldrich, I can either use the Aldrich stdev or I can use the measured stdev for the specific sample. How many measurements of a specific sample do I have to make before it becomes legit to trust the measured stdev for the sample rather than my long-term average for the Aldrich standard? Any pointers on how to work this out would be greatly appreciated - my supervisor is handwaving as "maybe ten?" but I'd like to have some kind of defensible reason for doing the thing...
kaberett: A sleeping koalasheep (Avatar: the Last Airbender), with the dreamwidth logo above. (dreamkoalasheep)
A [personal profile] noldo and [personal profile] kaberett production.

I watched Avatar: the Last Airbender for the first time in August 2011; [personal profile] noldo and [personal profile] mustela_nivalis were very encouraging, and very patient about my flailing.

At the beginning of season 2, I started writing fic for the first time in about eight years.

I got to the end and they pointed me at the Avatar: the Legend of Korra trailer, and I collapsed into a small puddle of hyperventilating squee.

So when The Promise was announced, I promptly put all of it on pre-order. Like, oh, pretty much every other fan with the finances to do so, I suspect.

And, d'you know, I was heartbroken. Sure, characters had the same names... but where's the Katara who, two minutes into the first episode of the first season of this mainstream USois kids' TV show, called a dude out for sexism and was taken seriously? Where's Toph interacting with Katara? Why is Mai relegated to ~the girlfriend~? Why is Sokka so bloody cissexist?

And that, boys and girls and everyone else, is when I got upset enough to go through the books and do a line-by-line count of who says what to whom.

By the power of [personal profile] noldo, I bring you the distressing results in the form of brightly-coloured graphics. So far I've only done counts for Books 1 & 2; Book 3 will follow on in the not-too-distant future. For these purposes, one "line" is approximately one speech bubble.

Part 1 )

Part 2 )

Summary


y so faily ;______________________________;

This show had such a great pattern of being incredibly feminist, and giving us actual complex developed - & developing! - female characters, who weren't defined solely by their interactions and relationships with the men of the series. Unfortunately - all my other issues with characterisation aside - as underlined by the statistics, that really, really doesn't carry across to the books.

Thoughts very welcome!
kaberett: Photo of a pile of old leather-bound books. (books)
It's very difficult, though, given how thoroughly sexist and racist and hereosexist (and anything else you care to think of) the undergraduate body is.

Exhibit A: Caltech's shocking lack of diversity: a microcosm for the United States?
Exhibit B: Diversity should mean more than just race, a shockingly under-researched, misrepresentative and inflammatory article by a Caltech undergraduate, published in the Caltech student press.

I've left a comment on the latter, which is currently in moderation. I reproduce it below.

This is the comment I left on the article. )

Stats

May. 15th, 2012 01:02 am
kaberett: Grinning emoticon. (:D)
  • one fall backwards
  • approximately 2.6 miles self-propelled
  • three blisters


I have a chair on loan from a friend. :D
kaberett: Photo of a pile of old leather-bound books. (books)
1. NPR's top 100 SF/Fantasy books. Bold if you've read, italicise ones you fully intend to read, underline if it's a book/series you've read part but not all of.

[Bold & italics indicates things I've read since first doing this meme.]

Read more... )

Of the authors mentioned in that meme, fourteen (23%) are women and sixty (77%) are men (none, to my knowledge, are non-binary). Of the women, one (7%) gets multiple mentions; 13 (21%) of men are mentioned more than once. Four (29%) of women get mentioned for series; twenty-one (35%) of men get mentioned for series. Also, everyone on that list is white, as far as I can tell. (Spreadsheet available on request.)

2. My books

By way of comparison, I tracked the books I read this year. I read somewhere in the region of 90-100 books, by 24 authors. 9 (38%) of the authors are male. One (4%) of the authors is trans.[1] One (4%) of the authors is non-white. Most of the books were series written by women.

My goal for the year was to actually read some books written by women, and I'm really glad of that: I read a bunch of stuff I really enjoyed but might not have got around to if I hadn't been ~being political~. This year: attempt to read (a) ANYTHING AT ALL IN GERMAN, and (b) books by people who aren't white.

[1] This would have been 2/25 - 8% - but circumstances intervened and I couldn't face it

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