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Hi

First of all your contribution is appreciated. by answering this question you have entered into process of my PhD Thesis. I need to analyze real experiences of new signals identification in your years of career as a technologist or R and D executive, innovation management, ...

weak signals are events that make senses that something new is going to emerge or some new deep changes are in the way...

have had you experienced such cases? a news! a photo! a conversation! a film! a patent! an investment! introduction of a product, ... these are examples of events that are primary signs of future change that we label it weak signal.

if you message me directly I will send you a questionnaire to get benefit of your knowledge in my PhD thesis.

Regards

Abouzar

I'm struggling to understand the significance of the fat-tailed distribution especially in career choice. 80000hours career guide argues that the more accurate distribution for career choice is the long-tailed one.

I'm trying to understand how the implication would differ between a normal bell-curve and a long-tailed distribution. My request: are the implications I wrote in "Part 2: Significance of the fat-tail distribution" accurate? Please focus on points 1 and 2.

Other Names: heavy-tailed distribution, long-tailed distribution, , pareto distribution

The guide is available for free download at https://80000hours.org/book/

"the most effective actions achieve far more than average. These big differences in expected impact mean that it’s really important to focus on the best areas. Of course, making these comparisons is really hard, but if we don’t, we could easily end up working on something with comparatively little impact. This is why many of our readers have changed which problem they work on. "p.60

"Each change took serious effort, but if changing area can enable you to have many times as much impact, and be more successful, then it’s worth it." (p.61)

"the top 10% of the most prolific elite can be credited with around 50% of all contributions, whereas the bottom 50% of the least productive workers can claim only 15% of the total work" (p. 89)

Simonton, Dean K. ʺAge and outstanding achievement: What do we know after a century of research?ʺ Psychological bulletin 104.2 (1988): 251 as cited in p.89 of 80000hours guide

"Areas like research and advocacy are particularly extreme, but a major study still found that the best people in almost any field have significantly more output than the typical person." Hunter, J. E., Schmidt, F. L., Judiesch, M. K., (1990) “Individual Differences

in Output Variability as a Function of Job Complexity”, Journal of Applied as cited in P.90 of 80000hours guide

"Moreover, success in almost any field gives you influence that can be turned into positive impact by using your position to advocate for important problems (p.91).

This all also means you should probably avoid taking a “high impact” option that you don’t enjoy, and lacks the other ingredients of job satisfaction, like engaging work". (p.91)

"Finally, because the most successful people in a field achieve far more than the typical person, choose something where you have the potential to excel. Don’t do something you won’t enjoy in order to have more impact. " (p.95)

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Figure Assumed (NOT actual) Bell-Curve for problems (p.59)

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Figure: Actual fat-tail distribution for problems (p.60)

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Figure: Actual Fat-Tail distribution of Careers (p.90)

1. It seems to me that in both distributions we have a motivation to aim for the top (obviously the top would be better) but the nature of motivation changes.

The nature of the carrot and stick changes from "aim to be among the best" because

(bell-curve carrot): if you do great things will happen to you.

(bell curve stick): if you don't, you will remain in the average and mean range

To" aim to be among the best" because

(fat-tail carrot): if you do, VERY VERY VERY great things will happen to you.

(fat-tail stick):If you don't, you will remain in the average (BELOW mean)

2. The more variance there is in a statistical sample, the wiser it is to aim to move to the exploration direction in the exploration-exploitation (deliberation-action) spectrum (the relationship between variance and value of new information). In terms of career, the variance is great so the exploration investment should be great as well.

3. Median does not equal average. The average could be misleading and the median could be misleading

4. If all other factors are moderate or weak but you have a good reason to think you can reach the top, go for it because average can be misleading, your rank is as important as your field).

5. Choosing a job at random is not advised because the median is lower than we think.

6. Even though below mean is much more likely in this distribution, probability of being a hyper-performer is higher , which makes the hyper-performer goal a more realistic goal hence, it's easier to become motivated by it.

7. Looking at the outliers becomes more important because they become more influential.

8. Pareto principle (80/20) can encourage generalist over specialization because the effort you put in one field result in a better impact if distributed over many fields but at the same time it can encourage specialization over generalism because the pareto distribution makes you want to aim for the very top because its impact is disproportionate.

9. Does the long-tailed distribution favor an "all-star" "super-star" or "SWAT" team approach of fewer more qualified people (quality over quantity)?

10. Prioritization becomes more important?

11. We often behave as if the bell-curve distribution is true while it's not. So the significance lies in adjusting our behaviour?

12. Why does personal fit become more important under the long-tailed distribution? Because the long-tailed distribution has a higher variance. If success in a specific field had zero variance, then individual differences wouldn't matter much so the person-environment fit would not be v. important because as persons change nothing changes as a result. However, the reality is that there is great variance so individual differences matter a lot (how would you "react" to a field NOT JUST how good is a career).

 The concept of employability appears to be relatively new and has been variously characterised as comprising the three dimensions of career identity, personal adaptability, and social and human capital (Fugate 2004) as well as openness to changes at work, work and career resilience, work and career proactivity, career motivation and work identity (Hennekam, 2013). To the extent that it reflects “the individual’s ability to keep the job one has, or to get the job one desires” (Rothwell et al, 2007) does it provides an indicator of the efficiency and effectiveness of a labour market?

“The protean career is driven by the person, not the organization, based on individually defined goals, encompassing the whole life space, and being driven by psychological success (rather than) objective measures of success such as pay, rank or power. It is a career in which the person is (1) values driven in the sense that the individual’s personal values provide the guidance and measure of success for the individual’s career, and (2) self-directed in personal career management—having the ability to be adaptive in performance and learning demands.”

Another result of these changes is the move towards more ‘boundaryless’ careers, which involve a sequence of job opportunities that go beyond single employment settings. It involves the breaking down of traditional boundaries (for example job boundaries of specialist functions and skills), organisational careers which progress independently of well trodden career paths and the social boundaries separating work and family roles.

Read more at http://www.sandboxadvisors.com/insights/well-being-advancement/protean-boundaryless-careers/#QwG3ESDH0TsWOBt7.99

Could you use additional ideas on your microplastic research?

I'm happy to share a draft of a project on impacts of microplastic on terrestrial biodiversity & function. It received positive feedback, but we can't execute it due to changes in my career perspectives. Please feel free to copy or chery pick whatever suits best your interest. The important is that research goes on. ;)

HI, my research interests are focused on weather and climate extremes, climate variability and changes, and so on. Now, I am looking for a visiting scientist position to borden my academic career. So, whose group has this kind position with funding? If yes, please contact me as soon as possible, I would like to talk with you about the details on visiting things.

Thanks a lot!

The key films are A Date for Mad Mary, Dare to be Wild and The Hit Producer other film can be used

1. Can you identify any and comment on strong female characters in contemporary Irish films?

2. Was the female character fairly portrayed in terms of career, ability and status, are female characters stereotyped?

3. Do you think that women are misrepresented as having inadequate skills and abilities necessary to pursue a career?

4. What changes do you believe should be effected to ensure a fair, more balanced representation of women in film.

Any help and opinions are greatly appreciated.

Since my early career research focused on the search for biomarkers, particularly red blood cell Li-Na countertransport levels in bipolar patients and alcoholic patients, and many of my bipolar patients also had clinical complaints consistent with what is now called fibromyalgia; and my mid-career research focused more on the epidemiology and mental health aspects of HIV infection, through the Multicenter AIDS Cohort Study (the MACS), it is interesting to see other researchers interested in immune function in both affective disorders and fibromyalgia. Have you or any other researchers following your research also seen similarities in the immune profiles of patients with bipolar disorder and fibromyalgia and the state-dependent changes in immune markers?

Recreational and scientific scuba diving are for me insatiable passions. However, it came to my mind that we are currently experiencing a shift in underwater data acquisition thanks to the development of AUV, ROV, surface drones and acoustic methods. This interest is also linked with a shift in my career going from extensive underwater sampling by scuba diving to remote sensing by acoustic methods and the awareness that came with it. So my (heartbreaking) opened question foreseeing the end of the scuba diving era within few decades.

What is your feeling about this?

Which fields see the fastest changes?

Which remote or automated techniques already exist or will emerge?

Dear Professor Amy Shuen,

I am a researcher from Finland (Lappeenranta University of Technology). Before academia I did a long career in the media. Now I am studying dynamic capabilities in the media context. So far I have done case studies. But I am interested in studying dynamic capabilities on industrial level, because it seems that the changes are following similar paths and logic in the media industry. On the other hand and based on the nature of dynamic capabilities, they are firm-specific and always tailored to their context. But can a specific industry be seen as a context which gives rise to certain kinds of dynamic capabilities?

I would be very interested in your thoughts.

Best regards,

Päivi Maijanen-Kyläheiko