How to read and understand a scientific paper: a guide for non-scientists « Violent metaphors

I only wish I had been this organized and diligent when I was doing the research for my dissertation. Or that I had had this kind of excellent advice available when I did. 

How to read and understand a scientific paper: a guide for non-scientists « Violent metaphors: “What constitutes enough proof? Obviously everyone has a different answer to that question. But to form a truly educated opinion on a scientific subject, you need to become familiar with current research in that field.  And to do that, you have to read the ‘primary research literature’ (often just called ‘the literature’). You might have tried to read scientific papers before and been frustrated by the dense, stilted writing and the unfamiliar jargon. I remember feeling this way!  Reading and understanding research papers is a skill which every single doctor and scientist has had to learn during graduate school.  You can learn it too, but like any skill it takes patience and practice.

I want to help people become more scientifically literate, so I wrote this guide for how a layperson can approach reading and understanding a scientific research paper. It’s appropriate for someone who has no background whatsoever in science or medicine, and based on the assumption that he or she is doing this for the purpose of getting a basic understanding of a paper and deciding whether or not it’s a reputable study.”

While excellent advice in its own right, this blog post is also a reminder that knowledge work requires some pretty sophisticated skills and those skills require practice to develop and maintain.

Wise advice—hard practice. Do the work—share it.

I discovered this in the usual way—by ignoring the advice and following a trail of breadcrumbs that started on Facebook. I’ve paired this talk by Neil Gaiman with a related one by Ira Glass below. I wanted to have both of them ready to hand when I needed some encouragement and a kick in the ass.

Gaiman’s closing advice: ‘Be wise, because the world needs more wisdom. And if you cannot be wise pretend to be someone who is wise — and then just behave like they would.'”

Neil Gaiman Addresses the University of the Arts Class of 2012 from The University of the Arts (Phl) on Vimeo.

 

(Via Neil Gaiman Says It Better (Video) | On Being.)

Here is Ira Glass with a similar set of observations and advice:

Eleven Years and Counting at McGee’s Musings

Yesterday marked the eleventh anniversary of the first blog post on McGee’s Musings in 2001.

In two weeks, we’ll practice the American version of democracy, choose a President, revolution will not occur regardless of who wins and, despite the rhetoric, life will go on. We (the U.S. and the rest of the planet) will still face a variety of wicked problems. 

Getting smarter about how we work as individuals, teams, crowds, competitors and the like remains a priority. My efforts in that regard haven’t yet worked their way to visibility here, but they will. Being part of the conversation is important. Listening is half of the process (maybe more). 

As always, my thanks to all of those who’ve been part of the interesting conversations that have taken place over the past year. 

KM Chicago: Collaborating Minds: Solving Tough Problems with a Unique Team

David and I will be talking about the work we’ve been doing on collaboration at next week’s KM Chicago meeting. We’re looking to have a highly interactive session. 

KM Chicago: Collaborating Minds: Solving Tough Problems with a Unique Team: ” Thursday, August 30, 2012 Collaborating Minds: Solving Tough Problems with a Unique Team At 5:30 on Tuesday, September 11th, join Jim McGee and David Friedman at KM Chicago’s monthly meeting to hear a progress report on ‘Collaborating Minds’, their unique problem-solving venture. This meeting will be especially productive in person, but participation online is also available. See details on the right.   As Jim points out, we continue to make progress in developing tools to support the efforts of teams to conduct complex knowledge work. At the same time, we are deepening our understanding of what differentiates highly effective teams from average teams. But these two streams of progress rarely intersect.   Collaborating Minds is the business concept that Jim and Dave have developed that functions at that intersection of complex knowledge work and highly effective teams.    Collaborating Minds tries to answer three related questions:

1. Given what we know about high-performance teams and current social technologies, can we create a virtual high-performance team with several hundred members?

2. If such a team existed, what kinds of problems could it solve that are currently unsolved?

3. Is there an acceptable business model to sustain that team over time?

On September 11th Jim and David will tell us what they’ve learned to date and will lead participants in a design collaboration that will help shape Collaborating Minds’ next stage of development.

Headshot DavidFriedmanDavid Friedman is passionate about problem-solving and about relationship building as fundamental human activities. That’s why he’s developing Collaborating Minds. He wants people to be much more productive and enjoy themselves much more too. He writes about collaboration at Positive Structures.  David was a partner at McKinsey & Company (a global consulting firm) and through his firm Bridgewell Partners has advised professionals on growing their practices through systematic relationship building. You can contact David here.  

 

 

McGeeJimHeadshot 20120807Jim McGee is an expert in knowledge management and knowledge use. He also knows a lot about technology, and about where technology and knowledge work intersect (or should). That’s why he’s a founder of Collaborating Minds. He’s been writing about these topics since 2001 at McGee’s Musings. Jim was a founder of Diamond Technology Partners (a technology and management consulting firm) and has been, among other roles, a faculty member at the Kellogg School at Northwestern University. You can contact Jim here. Posted by KMChicago at 5:15 PM “

Richard Feynman On The Folly Of Crafting Precise Definitions

I’ve often struggled with the notion of definitions when working in organizations. On the one hand, too many of us hide our ignorance and uncertainty behind a wall of jargon and terminology. Terms fall in and out of favor and their relationship to the underlying real world is often less important than their value from a marketing perspective.

On the other hand, new terms and language can help us point to and see new ideas and new opportunities for action. Here’s a recent post from Bob Sutton that sheds light on these challenges and is worth thinking about.

One of my best friends in graduate school was a former physics major named Larry Ford. When behavioral scientists started pushing for precise definitions of concepts like effectiveness and leadership, he would sometimes confuse them (even though Larry is a very precise thinker) by arguing “there is a negative relationship between precision and accuracy.” I just ran into a quote from the amazing Nobel winner Richard Feynman that makes a similar point in a lovely way:

We can’t define anything precisely. If we attempt to, we get into that paralysis of thought that comes to philosophers one saying to the other: “you don’t know what you are talking about!”. The second one says: “what do you mean by talking? What do you mean by you? What do you mean by know?

Feynman’s quote reminded me of the opening pages of the 1958 classic “Organizations” by James March (quite possibly the most prestigious living organizational theorist, and certainly, one of the most charming academics on the planet) and Herbert Simon (another Nobel winner). They open the book with a great quote that sometimes drives doctoral students and other scholars just crazy. They kick-off by saying:

“This is a book about a theory of formal organizations. It is easier, and probably more useful, to give examples of formal organizations than to define them.”

After listing a bunch of examples of organizations including the Red Cross and New York State Highway Department, they note in words that would have pleased Feynman:

“But for the present purposes we need not trouble ourselves with the precise boundaries to be drawn around an organization or the exact distinction between an “organization” and a “non-organization.” We are dealing with empirical phenomena, and the world has an uncomfortable way of not permitting itself to be fitted into clean classifications.”

I must report, however, that for the second edition of the book, published over 20 years later, the authors elected to insert a short definition in the introduction:

“Organizations are systems of coordinated action among individuals and groups whose preferences, information, interests, or knowledge differ.”

When I read this, I find myself doing what Feynman complained about. I think of things they left out: What about norms? What about emotions? I think of situations where it might not apply: Doesn’t a business owned and operated by one person count as an organization? I think of the possible overemphasis on differences: What about all the times and ways that people and groups in organizations have similar preferences, information, interests, and knowledge? Isn’t that part of what an organization is as well? I could go on and on.

I actually think it is a pretty good definition, but my bias is still that I like original approach, as they did such a nice job of arguing, essentially, that if they tried to get more precise, they would sacrifice accuracy. Nonetheless, I confess that I still love trying to define things and believe that trying to do so can help clarifying your thinking. You could argue that while the outcome, in the end, will always be flawed and imprecise, the process is usually helpful and there are many times when it is useful pretend that you have a precise and accurate definition even if you don’t (such as when you are developing metrics). “

Richard Feynman On The Folly Of Crafting Precise Definitions – Bob Sutton:

Euan Semple on nurturing a knowledge ecology

This gem from Euan Semple made the rounds earlier this summer. I was too busy then to do more than note it.

Ten ways to create a knowledge ecology

TUESDAY, JUNE 28, 2011 AT 7:08AM

A tweet yesterday prompted me to remember sage advice from Dave Snowden which I took to heart in my work with social tools at the BBC. “You can’t manage knowledge but you can create a knowledge ecology”. I thought it might be useful to others to list the ten most important things I learned about doing this.

1, Have a variety of tools rather than a single system. Not everyone sees the world the same way or has the same needs so mixing up different tools with different strengths allows people to find one that works for them. Avoid single platforms like the plague.

2. Don’t have a clear idea where you are headed. The more fixed you are in your aspirations for your ecology the less likely you are to achieve them. Be prepared to go where people’s use of the tools takes you and enjoy the ride.

3. Follow the energy. Watch where the energy in the system is and try to copy the factors that generated it. Get others interested in why energy emerges and they will want some of it themselves.

4. Be strategically tactical. You can have an overall strategy of behaving in certain ways depending on how your ecology develops. It is possible to sell this as a strategy to those who need strategies.

5. Keep moving, stay in touch, and head for the high ground. Keep doing things, keep talking about what you are doing and why, and have a rough idea of where the high ground is.

6. Build networks of people who care. Don’t try to manage your ecology by committee but cultivate communication and trust between those who care that it works and have the commitment to do something about it – whoever they are and whatever their role.

7. Be obsessively interested. Notice everything that happens and consider why. Tell great stories about what you are observing.

8. Use the tools to manage the tools. Blog about what is going on with your corporate blogging, ask questions in your forum about security, tweet when something is changing in your ecology and ask people why it is interesting.

9. Laugh when things go wrong. If you are pushing limits and exploring new territory things will occasionally blow up in your face. Having a sense of humour and enjoyment of the absurd will help you stay sane.

10. Unleash Trojan Mice. Don’t do big things or spend loads of money. Set small, nimble things running and see where they head.

(– The Obvious? – Ten ways to create a knowledge ecology)

The paradox of organic approaches to change is that while they appear to be simple and mundane, they also appear to be the only thing that works with any regularity in complex situations. For all the rhetoric of bold plans and audacious goals, the reality is that most change occurs inch-by-inch.

Where IS Health Care Going? Technology Leader’s Presentation

Last week, JoAnn Becker  and I ran an interactive discussion with the monthly TLA Manager’s breakfast meeting here in Chicago. We had a lively and excellent debate among a group of technology executives, health care executives, and other smart people about the real challenges of successfully deploying information technology to improve productivity and quality in delivering health care in this country.

That, of course, is an immense issue and would could barely scratch the surface in the hour we had. For those who are interested, we’ve uploaded our slides to Slideshare.

 

We used two recent TV ads from GE and IBM to kick off the discussion. On the surface, each provides a sense for the promise of information technology to make health care more effective:

GE TV ad – Doctors
IBM TV Ad – “Data Baby”

In the tradition of all good technology vendor advertising, both also completely gloss over the complex organizational adaptation and evolution necessary to bring these hypothetical worlds into being. They also gloss over the existing institutional and industry complexity that needs to be understood and addressed through a combination of design, leadership, and management.

Fred  Brooks, professor of computer science at UNC and author of The Mythical Man-Month : Essays on Software Engineering, draws a critical distinction in the final chapter of the book, which is titled "No Silver Bullet," between accidental and essential complexity. His point is that software is so difficult to design and develop because it must successfully model the essential complexity of the domain it addresses. Technology and software efforts can stumble on a variety of barriers and roadblocks, but failing to understand and address essential complexity is the worst.

Health care provides its own mix of accidental and essential complexity. If the decision makers aren’t careful to draw distinctions between accidental and essential, then a great deal of time and effort will be expended without corresponding returns. On the one hand, we may simply succeed in "speeding up the mess" as my friend Benn Konsynski so liked to put it. Or, we may obliterate  essential complexities in a quest for uniformity and productivity that is blind to those complexities. Or, finally, we may invest the appropriate level of design time and talent in systems that account for essential complexity and eliminate accidental complexity.

Resources

We drew on a variety of excellent resources in preparing for this talk and wanted to make them more easily available here.

Here are several books that provide useful context and background

Here are pointers to a variety of health care related web resources worth paying attention to:

Collaboration, games, and the real world

I’ve been thinking a lot about hard problems that need multiple people collaborating to solve. There’s no shortage of them to choose from.

This TED video from Jane McGonigal makes a persuasive case that I need to invest some more time looking at the world of online gaming for insight. Watch the video  and see if you don’t come to a similar conclusion.