With all due respect to these studies, it’s safe to say that PA (Passive Aggresive –gian) behavior is problematic and annoying. But whether it deserves to be defined as a bona fide mental illness — and subsequent stigmatization in society at large — seems debatable. Calls to restore its place as a formal pathology are indicative of the struggles of psychiatry to justify its (often qualitative, normative) definitions of mental illness. It’s important to draw a line between pathologizing PA behavior and figuring out how to deal with difficult individuals in one’s life. What’s more, it risks pathologizing compliant defiance in the face of authority, whether it be work-to-rule actions, the Occupy Movement, or (sadly) a potentially abusive home or work environment.
via The Secrets To Handling Passive-Aggressive People.
What’s a mid-career software engineer actually worth? Try $779,000 per year as a lower bound. | Michael O. Church
I would argue, even, that programmer salaries are low when taking a historical perspective. The trend is flat, adjusting for inflation, but the jobs are worse. Thirty years ago, programming was an R&D job. Programmers had a lot of autonomy: the kind of autonomy that it takes if one is going to invent C or Unix or the Internet or a new neural network architecture. Programmers controlled how they worked and what they worked on, and either answered to other programmers or to well-read scientists, rather than anti-intellectual businessmen who regard them as cost centers. Historically, companies sincerely committed to their employees’ careers and training. You didn’t have to change jobs every 2 years just to keep getting good projects and stay employable. The nature of the programming job, over the past couple decades, has become more stressful (open-plan offices) and careers have become shorter (ageism). Job volatility (unexpected layoffs and, even, phony “performance-based” firings in lieu of proper layoffs, in order to skimp on severance because that’s “the startup way”) has increased. With all the negatives associated with a programming job in 2014, that just didn’t exist in the 1970s to ’80s, flat performance on the salary curve is disappointing. Finally, salaries in the Bay Area and New York have kept abreast of general inflation, but the costs of living have skyrocketed in those “star cities”, while the economies of the still-affordable second-tier cities have declined. In the 1980s and ’90s, there were more locations in which a person could have a proper career, and that kept housing prices down. In 2014, that $142,000 doesn’t even enable one to buy a house in a place where there are jobs.
via What’s a mid-career software engineer actually worth? Try $779,000 per year as a lower bound. | Michael O. Church.
The trajectory of a software engineer… and where it all goes wrong. | Michael O. Church
The scale I’m about to define comes from one insight about human organizations. Teams, in general, have four categories into which a person’s contribution can fall: dividers, subtracters, adders, and multipliers. Dividers are the cancerous people who have a broad-based negative effect on productivity. This usually results from problems with a person’s attitude or ethics– “benign incompetence” (except in managers, whose job descriptions allow them only to be multipliers or dividers) is rarely enough to have a “divider” effect. This is an “HR issue” (dividers must improve or be fired) but not the scope of this professional-development scale, which assumes good-faith and a wish for progress. Subtracters are people who produce less than they cost, including the time of others who must coach and supervise them. As a temporary state, there’s nothing wrong with being a subtracter– almost every software engineer starts out his career as one, and it’s common to be a subtracter in the first weeks of a new job. Adders are the workhorses: competent individual contributors who deliver most of the actual work. Finally, multipliers are those who, often in tandem with “adder” contributions, make other people more productive. In many industries, being a multiplier is thought to be the province of management alone, but in technology that couldn’t be farther from the truth, because architectural and infrastructural contributions (such as reusable code libraries) have a broad-based impact on the effectiveness of the entire company.
via The trajectory of a software engineer… and where it all goes wrong. | Michael O. Church.
rePost::How Companies Learn Your Secrets – NYTimes.com
Once I figured out all the parts of the loop, it seemed fairly easy to change my habit. But the psychologists and neuroscientists warned me that, for my new behavior to stick, I needed to abide by the same principle that guided Procter & Gamble in selling Febreze: To shift the routine — to socialize, rather than eat a cookie — I needed to piggyback on an existing habit. So now, every day around 3:30, I stand up, look around the newsroom for someone to talk to, spend 10 minutes gossiping, then go back to my desk. The cue and reward have stayed the same. Only the routine has shifted. It doesn’t feel like a decision, any more than the M.I.T. rats made a decision to run through the maze. It’s now a habit. I’ve lost 21 pounds since then (12 of them from changing my cookie ritual).
via How Companies Learn Your Secrets – NYTimes.com.
rePost::The Quiz Daniel Kahneman Wants You to Fail | Business | Vanity Fair
5a. Choose between getting $900 for sure or a 90 percent chance of getting $1,000.
A. Getting $900
B. 90 percent chance of getting $1,000
5b. Choose between losing $900 for sure or a 90 percent chance of losing $1,000.
A. Losing $900
B. 90 percent chance of losing $1,000
Hide explanatory note ↑
The results of this simple problem set, for which most participants answer A and then B, were used to develop the thesis that would make Kahneman and Tversky famous: prospect theory. In a 1979 paper, they documented a peculiar behavioral tendency: when people faced a gain, they became risk averse; when they faced a loss, they became risk seeking. As a result of their discovery, Kahneman and Tversky debunked Bernoulli’s utility theory, a cornerstone of economic thought since the 18th century. (Bernoulli first proponed that a person’s willingness to gamble a certain amount of money was a product of how that amount related to his overall wealth—that is, $1 million means more to a millionaire than it does to a billionaire.)
Along with playing a large role in Kahneman’s being awarded the Nobel Prize in 2002, the theory also spawned a new academic pursuit, the field of behavioral economics. Prospect theory, Michael Lewis writes, explains “why people are less likely to sell their houses and their stock portfolios in falling markets; why, most sensationally, professional golfers become better putters when they’re trying to save par (avoid losing a stroke) than when they’re trying to make a birdie (and gain a stroke).”
via The Quiz Daniel Kahneman Wants You to Fail | Business | Vanity Fair.
Experiment of The Day :: People In Doubt Of Their Closely Held Beliefs Advocate Their Beliefs More???
I think this is a perfect post for the Freethinkers page.
Across three experiments, people whose confidence in closely held beliefs was undermined engaged in more advocacy of their beliefs (as measured by both advocacy effort and intention to advocate) than did people whose confidence was not undermined. The effect was attenuated when individuals affirmed their beliefs, and was moderated by both importance of the belief and open-mindedness of a message recipient. These findings not only have implications for the results of Festinger’s seminal study, but also offer new insights into people’s motives for advocating their beliefs.
Learned :: How to Increase Your Self-Control Without Really Trying | PsyBlog
Automatic, unconscious self-control
The results showed that, when participants were thinking concretely, they tended to unconsciously see candy bars in a positive light and apples in a negative light. But this was reversed when participants were thinking abstractly. Just as predicted, abstract thinking automatically made people unconsciously think of candy bars as the devil’s own food.
To back this up they asked participants in the two conditions whether they would like an apple or a candy bar, right now. They found that when participants were thinking in a concrete low-level way, they chose the apple over the candy bar only 50% of the time. But when they were thinking abstractly this percentage shot up to 76%. Not bad for such a simple manipulation.
via How to Increase Your Self-Control Without Really Trying | PsyBlog.
What Do Men Look For In Women!!! :: Does Playing Hard to Get Work? | PsyBlog
things to ponder…. hmm mismo???
The woman who was apparently selectively hard to get, i.e. easy for you but hard for everyone else was the runaway winner for the men. Not only that but men thought the selectively hard to get woman would have all the advantages of the easy to get woman with none of the drawbacks of the hard to get woman. They thought she would be popular, warm and easygoing, but not demanding and difficult.
via Does Playing Hard to Get Work? | PsyBlog.
rePost::Seth's Blog: Hunters and Farmers
This is an interesting perspective. Though I’ve been very wary of Evolutionary Psychology/Neurology/Anything concerning the brain, I am drawn to this idea. I believe this is another form of the more nuanced view in the book by probably 5th most favorite TED talk speaker sir Ken Robinson (ted Talk here) . I embedded the talk at the end of this post. Hope you can read his book The Element: How Finding Your Passion Changes Everything.
Clearly, farming is a very different activity from hunting. Farmers spend time sweating the details, worrying about the weather, making smart choices about seeds and breeding and working hard to avoid a bad crop. Hunters, on the other hand, have long periods of distracted noticing interrupted by brief moments of frenzied panic.
It’s not crazy to imagine that some people are better at one activity than another. There might even be a gulf between people who are good at each of the two skills. Thom Hartmann has written extensively on this. He points out that medicating kids who might be better at hunting so that they can sit quietly in a school designed to teach farming doesn’t make a lot of sense.
A kid who has innate hunting skills is easily distracted, because noticing small movements in the brush is exactly what you’d need to do if you were hunting. Scan and scan and pounce. That same kid is able to drop everything and focus like a laser–for a while–if it’s urgent. The farming kid, on the other hand, is particularly good at tilling the fields of endless homework problems, each a bit like the other. Just don’t ask him to change gears instantly.
Marketers confuse the two groups. Are you selling a product that helps farmers… and hoping that hunters will buy it? How do you expect that people will discover your product, or believe that it will help them? The woman who reads each issue of Vogue, hurrying through the pages then clicking over to Zappos to overnight order the latest styles–she’s hunting. Contrast this to the CTO who spends six months issuing RFPs to buy a PBX that was last updated three years ago… she’s farming.
via Seth’s Blog: Hunters and Farmers.
Advice:: Ten Simple Rules for Choosing between Industry and Academia
Rule 7: Plan for the Long Term Top
Having noted the current situation in Rule 6, it's important also to say that a career decision should be made with the long haul in mind. The business cycle will eventually reverse itself, and while the business model may need to change irrevocably, the aging population alone dictates that healthcare will be an increasing global priority. Likewise, history shows that growth in government funding for science waxes and wanes, with a time constant somewhat longer than a decade. Trying to optimize a career decision based on current conditions is a bit like trying to time the stock market—you are sure to be overtaken by events.
One approach is to choose some reasonably long time frame, perhaps a decade, and ask yourself whether you'd be content to have lived through the average ups and downs you'd experience in a given job over that period. In academia, that would include a tenure decision (rate your chances), a lot of grant applications with mixed success at best, and maybe some great students and really significant scientific contributions. In pharma or large biotech, it would encompass a couple of promotions, your own group and maybe a department, at least one merger or other big disruption, and several rounds of layoffs. In small business, it might include a failed startup (or two, or three), an IPO if you're lucky, and a lucrative exit strategy or long-term growth if you're really lucky.
If you game these scenarios with various probabilities, and use your imagination, it just might become clear which ones you have no stomach for, and which ones really hold your interest.
via PLoS Computational Biology: Ten Simple Rules for Choosing between Industry and Academia.
There was an aha moment when I got this. I used to plan. In planning I count myself as topnotch. I coupled this with an extremely frank, honest evaluation after. Repeatedly doing this It hit me that as Dwight Eisenhower said
“In preparing for battle I have always found that plans are useless, but planning is indispensable.”
“Plans are nothing; planning is everything.”
See, it hit me that as things become more complicated the more useless plans become. To be really rational about something what you need to do is develop a personality of adaptability. To be a person that can face most of anything. To train yourself to be quick on your feet, and great at improvisation. We can guess a lot of things about the future we can see trends and have a feel for what is happening, But in a sense predicting the future is simply impossible. This help wean me from believing that there is a yellow brick road to a happy/successful life. I’m no longer blind to believing that anything is a sure thing. Most things for me are probable or improbable.
Life is not as clean as that of science or math. Yes you can use some optimization, game theory and stuff but the complexity in life sometimes mean that even if you optimize from start to finish you end up somewhere not so good, whilst even if you made so many mistakes and bad decisions you still end up someplace great. Life is choatic.
Does this mean I don’t plan? No, I still plan during times when I don’t have anything better to do. This is because planning is everything. It is aform of play acting. It’s probably my excuse for perusing science fiction, to put myself in situations where making decisions does not follow simple rules.
If all things fail, cheer up always remember that the human mind has an extreme ability to be okay with most things. Just ask Dan Ariely(In his 2005 TED Talk I think.)