Peer-review practices of psychological journals: The fate of published articles, submitted again

The present investigation was an attempt to study the peer-review process directly, in the natural setting of actual journal referee evaluations of submitted manuscripts. As test materials we selected 12 already published research articles by investigators from prestigious and highly productive American psychology departments, one article from each of 12 highly regarded and widely read American psychology journals with high rejection rates (80%) and nonblind refereeing practices.

With fictitious names and institutions substituted for the original ones (e.g., Tri-Valley Center for Human Potential), the altered manuscripts were formally resubmitted to the journals that had originally refereed and published them 18 to 32 months earlier. Of the sample of 38 editors and reviewers, only three (8%) detected the resubmissions. This result allowed nine of the 12 articles to continue through the review process to receive an actual evaluation: eight of the nine were rejected. Sixteen of the 18 referees (89%) recommended against publication and the editors concurred. The grounds for rejection were in many cases described as “serious methodological flaws.” A number of possible interpretations of these data are reviewed and evaluated.

In the US e-book is reading YOU

For centuries, reading has largely been a solitary and private act, an intimate exchange between the reader and the words on the page. But the rise of digital books has prompted a profound shift in the way we read, transforming the activity into something measurable and quasi-public.

The major new players in e-book publishing—Amazon, Apple and Google—can easily track how far readers are getting in books, how long they spend reading them and which search terms they use to find books. Book apps for tablets like the iPad, Kindle Fire and Nook record how many times readers open the app and how much time they spend reading. Retailers and some publishers are beginning to sift through the data, gaining unprecedented insight into how people engage with books.
Your E-Book Is Reading You

И, до кучи, старое:
About a year after Pole created his pregnancy-prediction model, a man walked into a Target outside Minneapolis and demanded to see the manager. He was clutching coupons that had been sent to his daughter, and he was angry, according to an employee who participated in the conversation.

“My daughter got this in the mail!” he said. “She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?”

The manager didn’t have any idea what the man was talking about. He looked at the mailer. Sure enough, it was addressed to the man’s daughter and contained advertisements for maternity clothing, nursery furniture and pictures of smiling infants. The manager apologized and then called a few days later to apologize again.

On the phone, though, the father was somewhat abashed. “I had a talk with my daughter,” he said. “It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”

Раз, два.

It's what he would've wanted.

Детям, беременным и любителям котов не смотреть.
Описание с лепры: голландский художник Барт Янсен, используя приемы таксидермии, превратил труп своего погибшего под колесами кота в радиоуправляемый квадролёт.

Но кто тебя тащит за язык говорить всю правду

Ситуацию для «Нескучного сада» комментирует епископ Смоленский и Вяземский Пантелеимон, член ВЦС.
В этой кампании против Патриарха я еще вижу одну сторону: мне кажется, из-за нашей советской истории, из-за того что большевики когда-то силой пришли к власти, люди у нас потеряли правильное отношение ко всякой власти – потеряли почтение к тем, кто выше их. Современный человек не признает возможным уважительное отношение ни к какой к власти. И это тоже Хамова черта, я так думаю.

(no subject)

Стенфордские онлайн-курсы (уже 16 штук)

Я послушал Machine Learning (который на самом деле CS229a Applied Machine Learning, Andrew Ng) и Introduction to Artificial Intelligence (CS221, Peter Norvig and Sebastian Thrun). Они простенькие, ML - практика на Octave/Matlab без всякого математического обоснования практически, AI - обзор, по чуть-чуть всего. По сути, для меня это было лучше книги тем, что подгоняют каждую неделю, а то уже новое издание вышло, а я её так и не дочитал ;) Английский, опять же, впитывается помаленьку.

Эти курсы - настоящие стенфордские курсы в том смысле, что их студенты тоже по ним учатся (например, вот вход для студентов на ai-class:, только они ещё могут задавать вопросы и им надо делать проджекты, которые потом проверяются. В общем, убрано всё, что требует индивидуального подхода со стороны преподов.

Весной ожидается аналогичная вещь от MIT - MITx, они ещё обещают за небольшие деньги выдавать дипломы или сертификаты от имени MITx, если оно вдруг кому надо :)

Если без того, чтобы подгоняли каждую неделю, то есть Stanford Engineering Everywhere, в частности CS229 Machine Learning (уже с теорией). Ещё по ML послушать есть Machine Learning, Carnegie Mellon University, Tom Mitchell (via).

Ну и до кучи:
iTunes U,
Academic Earth,
MIT OpenCourseWare ,
Open Learning Initiative - Carnegie Mellon University,
Open Yale courses
и ещё много всего.