Michael Battalio

Sunday, December 25, 2016

15th Annual Christmas Mass Email

Greetings and Salutations, 
Welcome to the Fifteenth Annual Christmas Mass Email.  I hope this finds each and every one of you well.

I have been okay this year, but our current year seems to have been a struggle in some way for just about everyone else I know.  Whether your job stinks, you’ve lost someone close to you, or if the daily grind just seems to be more abrasive lately, this year has been long.  Perhaps your personal setbacks this year have been mild, or perhaps 2016 was unbelievably positive for you.  That is genuinely terrific, but I think a lot of us can sympathize with the observation that this has been a tough year for many people.  I am unsure how much longer our collective malaise will last, but here is what I do know:  each of us will continue to have good years and bad years, each with their own ups and downs.  The important part is to persevere through the bad and appreciate the good.

Despite sounding a bit sour, I am confident that each of us will come out of this downturn better for it.  The reason I have this confidence is that there is one positive that emerges out of struggle, and that is the impetus for introspection.  This is what I invite each of us to do at the close of this year regardless of whether this year has been difficult or fantastically wonderful for you.  Release yourself from the obvious platitudes, and instead really pause and consider what about this year could be improved.  Then respond to what you can change.  Do not accept that next year will be just as hard, or if this year was good, do not accept that next year cannot be better.  The usual cliché is that struggle is character building.  That’s certainly true to a point, but there is a tenuous line between the construction of character and pointless hardship.  I cannot speak to each of you individually in one letter, but what I do offer is a modicum of advice for everyone.  For those of you that had a difficult year, the pain and worry and fight will not last forever.  We will get through this, but do not let this confluence of misfortune slip by without learning from it.  Experience is how we cope with difficult years and how we appreciate the positive years.  For everyone else, I simply say look out for the people around you that are having a tougher time in life than you.  You’ll probably need to lean on them someday in return.

Finally, I want to reiterate something I said a few years ago.  Lately, our society has accentuated discord to an unsettling degree.  Antagonism seems to be the first response to any sort of disagreement instead of conversation.  I am of the opinion that people (in general) are not malicious.  Some may manifest evil traits, but no one is intrinsically malicious.  However, the prevailing assumption seems to be that because someone doesn’t agree with us, they must not only be wrong but also morally repugnant.  This does not mean I believe there is no objective truth.  I assuredly do, but we will never develop consensus on anything if we attack one another instead of trying to understand opposing viewpoints and logically and calmly arguing our own cherished attitudes.  Foremost, I am advocating tolerance and reflection as we are all more alike than we are different.  We are all a part of humanity – ideology, creed, and tribe cannot divide us unless we allow it.  Let’s just listen to one another.  I know we are all capable of patience and understanding, and those should be the highest goals we seek.


And there you go.  I putter along — only a few months of graduate school left.  Congratulations to those who have really done something amazing this year, whether it’s finishing a degree, getting married, starting a family, finding a new passion in life, or any other accomplishment.  But never be satisfied; always strive for more.  Always question, learn, grow; otherwise, what’s the point?
Enjoy the season, and give yourself some credit for making it as far as you have.  Reply to let me know how you’re doing and what you’ve accomplished.  Wanting to hear from each of you is half the reason I send this every year.


The requisite joke:

A high school senior was taking his girlfriend to prom.  In preparation, he first went to rent a tuxedo.  Upon arriving at the shop, there was an enormously long line.  However, after a multi-hour wait, he did manage to get a beautifully tailored tuxedo.
Afterwards, he traveled to a nearby florist to pick up a corsage.  Once again, there was a line, but after a long wait, he was successful in selecting a magnificent cattleya orchid.
For his last task, he proceeded to rent a limousine, as this was his senior prom, and his date was a very special girl.  Though as his luck would have it, there was another extended line again, but his patience paid off, and he procured a luxurious car.
Several hours later, he and his date arrived to the prom hand-in-hand in style.  They talked and danced for a little bit, and then his girlfriend asked for some punch.  He went to get it, but there was no punch line.


Best wishes and happy holidays,

Sunday, July 10, 2016

My politics (part 9): guns – part 2

This series deals with some of my stances on political affairs and topics of the day.  I am quite liberal on some issues, but more conservative with others.  I self identify as an independent, but I definitely lean left.  I hesitate to do this, but I need to write a few posts about gun control.  I continue by addressing the common argument of many in the gun lobby.

Another trope used by the gun lobby is that the only way to stop a bad guy with a gun is a good guy with a gun (The NRA even sells a t-shirt [in black and navy] with those words.).

Ignoring the obvious reasons (that you need to have some training to not freeze up and be accurate)  Here are two reasons that argument is a fallacy.

1.)  It isn’t always clear who the bad guy is.
2.)  you have to be lucky or as well armed as the bad guy.

Even the police sometimes have a difficult time defining who the bad guy is (see e.g. Tamir Rice).  I do not trust a random civilian to make the determination in an active shooting situation that I’m an innocent and the guy next to me is bad (or not).  Humans are twitchy and have unreliable senses and interpretation.  This is especially true under duress.

For the sake of argument, let us now say the good guy has beyond a doubt selected the bad guy.  With adrenaline pumping through his veins, how well or quickly will he hit the selected bad guy?  The article I linked to in guns part 1 about the “need” for AR 15’s submits that the way to hit someone is to shoot as many projectiles as possible in the direction of the shooter.  For that to happen with a chance of the bad guy getting hit before the good guy, the good guy either needs a lot of luck or a weapon of a similar or higher bullet spraying ability as the bad guy.  If concealed handguns become ubiquitous (as many in the gun lobby want), then shooters wanting to maximize their impact will move to semi-automatic or automatic weapons (recent events would suggest that trend has already started).  Then, the good guy will need to increase his arsenal to compensate.  This creates an arms race between the bad guys and the “good” guys who want to be able to protect themselves if a situation ever arises where a gun might be useful.  (Anecdotally, here’s a devastated father who now wants to carry a gun because he’s afraid of others who do.)

Let me be clear, I am not an advocate of a ban on handguns or rifles.  I want to ban the escalation of weaponry that is becoming ever more efficient at killing people.  There are instances where people protected themselves by having a gun on their person (again anecdotally, I have a close family member that did so.).  But, the continued escalation of violence will only be curtailed if we draw the line somewhere.  We can discuss where that line is, but there needs to be a line where some guns are legal and some are not.

Friday, June 17, 2016

My politics (part 8): guns – part 1

This series deals with some of my stances on political affairs and topics of the day.  I am quite liberal on some issues, but more conservative with others.  I self identify as an independent, but I definitely lean left.  I hesitate to do this, but I need to write a few posts about gun control.  I begin by addressing the argument of someone against banning of semi-automatic weapons.

The US has more guns per capita than any other nation (by far), and at the same time the homicide rate in the US is the highest of western, industrialized nations.  (I recognize that the claim that the US has more mass shootings is not entirely correct.).  Correlation is not causation, but at this point, we have to try some fix, even if we aren’t sure of the causation.  (because, thanks gun lobby, the CDC hasn’t been able to fund research in to guns)

Here’s an article trying to articulate why some people “need” a semi-automatic riffle.  The gist of it is the AR platform is highly customizable and so it is like a toy.  This is a terrible argument.  I get that most people with guns are reasonable, well-adjusted people.  I get that shooting at the gun range more quickly and with a higher caliber is more fun than shooting slowly with a pellet gun in the same way that driving a sports car fast is more fun than driving a minivan slowly.  I get that tinkering is fun.  However, in the same way that we regulate all cars because the people who drive fast also more frequently drive dangerously, then we have to regulate the more “powerful” guns due to few dangerous wielders of any guns.  If your hobby or toy can kill people, the rest of us get a say in how you participate in your hobby.  This is becoming true with drones as well.  Only a few people are perverting the hobby, but because we have to control those deviants for the good of society, everyone must give up a bit of their freedom.   That’s the cost of civilized society.  I do not advocate an outright ban on these more deadly arsenals as I’m a realist and know that will never happen.  However, as the lethality of a weapon increases, the difficulty to legally obtain that weapon should increase in due course.  We can argue about the implementation of that difficulty through waiting periods and background checks or psychological evaluations, but this whole non starter position of “I want the gun; you can’t have it; second amendment.” has crossed into ridiculousness. (not including the successful perversion of the second amendment by the NRA to read that everyone has a right to whatever weapons exist.  It says “well regulated” in the same sentence as “right…to keep and bear arms.”  It also says “militia” with the original idea that states should have militias to protect themselves from the federal government – not individual citizens can form their own arsenals to rival that of a militia.  For more, start with this recent article on the perversion of the second amendment and go down the rabbit hole.)  People kill people, but guns allow people to kill people a lot more efficiently.  That efficiency is what needs to be regulated.

More posts on gun control to (possibly) come.

Saturday, May 28, 2016

Serious conversations (part 69): What is science - part 7

This series is a continuation of my conversations with an atheist friend of mine.  These are my edited responses from that conversation.  The sixty-third – seventieth entries deal with the nature of science.

So far we’ve covered the hierarchy of the sciences, defined science, and given examples, but what about math?

While we’ve considered history a science is a very loose sense of the word, what place does math and purely theoretical efforts have in our description of science.  I think string theory is science.  Reviewing my definition that science is a systematic observation of nature to find facts to describe the universe, string theory fits that mold.  It is a description of existence governed by formulae.  The fact that there are no testable predictions does not disqualify it as a science.  Merely, it makes it less useful.  Just because we don’t have the technology to probe the planck length to determine if electrons are actually strings does not make it not a science.  If it turns out string theory is wrong, then yes, it is fun games with math, but that doesn’t mean it wasn’t science at the time.  The goal is still observation and description.  Science requires the proper means just as much as the ends.  It would become no different than the hypothesis of spontaneous generation.  It is ridiculous now but still science then.  Even in hindsight, it is still science.  A negative result is still a result.  A disproven hypothesis is still science.  Thusly string theory (and loop quantum gravity and other theories of physics revolving around the unification of forces that cannot and probably will not be disproven) are science.

Is math a science?  In my cursory survey of some philosophies of some mathematicians/scientists (if you want to kill an afternoon, google ‘is math a science’), I think that math is a governor of science but not a science itself.  Science requires math but not vice versa.  In science, there are laws that are discovered that are not influenced by the science itself.  We are attempting to reverse-engineer the universe.  In math, it can be the other way around.  A set of laws (axioms) is assumed, and then the consequences of those choices are explored.  Math is also aesthetic.  It can be beautiful; it is what provides the beauty of some string theories.  The symmetry of them is appealing. (Perhaps that is why so many theoreticians are enamored with it.)  So back to the definition of science:  it requires observation to describe reality.  Math does not necessarily do that; therefore it is not a science.  Math a describe possible realities including our own.  What gives us the reason to use a particular set of axioms?  Observation (i.e. science).  

Friday, May 06, 2016

Serious conversations (part 68): What is science - part 6

This series is a continuation of my conversations with an atheist friend of mine.  These are my edited responses from that conversation.  The sixty-third – seventieth entries deal with the nature of science.

We’ve previously spent a lot of space on who is a scientist.  Now I consider the hierarchy of the sciences.

  I also want to take a moment to comment on the hierarchy of science.  In my academic career I’ve gotten the general impression that physics looks down on the other sciences as being lesser, easier, and derivative.  This is somewhat true as all the other sciences are in some way or another applied physics.  (I also feel the disdain of pure theorists who look down on experimentalists.  That is a different conversation.)  One reason I’ve always been drawn to physics even though I’m reasonably happy as a atmospheric dynamist is that I feel that physics is somehow a higher pursuit, and at times I still regret having gone into atmospheric science in the first place when I think I would be much happier in particle physics or astrophysics.  I often wonder why it is I think like that.  It could perhaps be because of how late physics is taught it us in high school.  I was not formally introduced to physics until my senior year of high school, but we are taught biology, Earth science, and chemistry earlier.  This makes physics seem more advanced.  Or it could be because physics is less connected to the other science than other sciences are to each other (think of how connected biology is to chemistry).  

I’m still not satisfied on why physics is thought of as the highest pursuit.  I get that physics is more mathematically involved, and in many ways it is harder that the rest of the “hard” sciences.  But why is it harder?  Can it just because of the math required to understand or manipulate the theory?  Could it because it can be so counterintuitive at times?  I cannot think of any other field that can be more counterintuitive than quantum mechanics, mostly because all the other sciences deal with larger length scales.  I don’t think I’ll ever get a good answer on why I think physics is a “higher” pursuit.  It simply is.

Saturday, April 16, 2016

Discussions on Wealth (part 14): Chapter 7: summary and discussion

This discussion on wealth is an offshoot of  Serious Conversations parts 53 and 54.  We are considering the book  The Origin of Wealth by Eric D. Beinhocker.  (I do not profit from clicks).  (Ed.:  we will be taking the general format of outlining the major points of the chapter and then discussing what we believe to be important or intriguing points.)

This chapter is on networks and how networks can explain behavior in the economy (and a multitude of other human endeavors).  A network is made of edges, which connect different nodes.  For example in a company each division is a network, and each employee is a node.  The edges are meetings, emails, phone calls between the employees.  

The connectedness of networks can explain why a certain product will explode in use suddenly.  Its connectedness reaches a tipping point where the ratio of edges to nodes reaches 1 (there are more meetings than people in the company analogy above).  After this phase transition, a sparsely connected network becomes densely connected.  The example provided was how the internet suddenly because incredibly useful in the 1990s even though it had been around for decades (i.e. the internet became useful when there were more ways to connect people (webpages or content) than there were people on the internet.

By visualizing connections between US cities, we see that random networks have far fewer degrees of separation.  For example, in a regular, lattice grid, if a city was connected to its 4 closest neighbors, it might take as many as 30 connections to go from the east coast to the west, but if instead each city were randomly connected to four others, some connections would be long but some would be short.  The number of small connections would be the same as the number of medium or long connections.  Thus, you could connect the east and west coasts using one long connection and several short ones.

Boolean networks are discussed next.  Boolean networks have nodes that can either be in one of two states, 0 or 1.  Boolean networks are guided by three variables:  number of nodes, connectedness, bias of the rules.  
The number of states a network can be in scales as 2^N (N=number of nodes).  This means that the potential for novelty increases exponentially.  For example, say 10 people work at a coffee shop, that is only 4 orders of magnitude smaller than the number of people who work at Boeing, but the complexity of making a coffee to making a jet is many more than four orders of magnitude difference.  
This scaling is offset by the scaling of connectedness.  If on average a network has more than one connection per node, then as the number of nodes grows, connections will scale exponentially.  The number of interdependencies grows faster than the network itself.  As the interdependencies grow, changes on one side of the network can ripple to the other, and the more interdependencies there are, the better the chance that a positive change in one side of the network will lead to a negative change on another part grows too.  This can lead to a “complexity catastrophe.”  This is why large companies can’t innovate all that well.  “Densely connected networks becomes less adaptable as the grow.”  Hierarchical networks can ameliorate the complexity catastrophe by reducing the complexity of the connections and thus the number of connections.  It compartmentalizes networks within networks.  
At some point networks will go from spontaneous order to chaos as the average number of connections increases.  Bias is the parameter that describes the point at which a network will transition from order to chaos.  The higher the bias, the more predictable the output from a node will be.  For example if a boolean node had output of 90% 1 given a random input of 0 and 1, the node is biased towards 1.  In general, the higher the bias, the more connected a network can be before it transitions to chaos.  

The complexity catastrophe can explain bureaucracy.  No one deliberately designs it.  Instead, it happens because the individual divisions simply want to optimize their section of the network.  I’m fascinated that bureaucracy is another emergent property of networks.  It seems that a lot of negatives in society are simply the result of how out society is setup, and not only that it seems this might be the only way an efficient society could be set up.  

Friday, March 25, 2016

My politics (part 7): some presidential politics

This series deals with some of my stances on political affairs and topics of the day.  I am quite liberal on some issues, but more conservative with others.  I self identify as an independent, but I definitely lean left.  This is a stand-alone post on the Republican presidential candidates.  I wrote this post for a Facebook audience but realized at the end that it was too much for that medium.  I’m moving it here, mostly because almost no one reads this who would be offended by what I’ve said.

In the last few years I’ve tended to remain impartial in my posts here though I’m sure it is no secret that I’m quite liberal.  I’ve stopped posting liberal material because I know that I’m never going to convince anyone who disagrees with me to change their mind via social media.  Having said that I can respect people who disagree with me.  Conservatism has some good things to say regarding government.  I, for example, side with conservatives on the subject of raising the social security age and to some extent on gun control (though I go back and forth).  I can therefore respect people who vote those conservative principles by picking a Bush, Gilmore, Kasich, Christie, Graham, Pataki, or Paul.  I can even respect a vote for Rubio.  What I can’t understand is why a conservative or any human being would vote for Donald Drumpf.  He is not self-funded; he certainly is not honest.  While he surely speaks his mind, you never know if what he says now will remain consistent even in the short term.  I get that many are mad at government and want someone removed from the “establishment” to fix it, but he has no experience in government.  You wouldn’t ask a dentist to build a bridge or a plumber to perform open-heart surgery.  In the same way, a businessman (with dubious successes) should not be elevated to the presidency without some experience in governance (or rational thinking).  
I’ve often been called pretentious, and while I do consciously try not to be because I know it is off-putting, I realize that I occasionally come across that way.  I would like to now fully embrace my pretentious, elitist narcissism that some accuse me of to deliver this message:  If you vote for Donald Drumpf, you are not intelligent enough to know me.  I ask that you unfriend (or in the context of a blog, stop following) me.  You are not even worth my time to unfriend myself.  Drumpf is a manipulative, vindictive megalomaniac, and if any of you are not intelligent enough to notice that there is no hope for you.  I get the appeal of anti-political correctness, but he has openly and on the record advocated for committing war crimes (by murdering the families of ISIS members).  The man is evil.  End of Story.
He calls himself a uniter, but he if can make a reasonable person this mad at other people that I usually respect, how could he possibly unite anything?  He’s bad for the country.  And I must say this is in no way a hypocrisy from me when I criticize people who were all doom and gloom on Obama’s reelection.  This is different.  I would be hypocritical if I were saying this over a Rubio or Cruz nomination (though I truly don’t think they would be good presidents).  I am not saying that though.  Drumpf is a different animal altogether.  If he is elected, he will take our country down a path that I do not see ending well for anyone of any political persuasion.  

Republicans:  VOTE AGAINST DRUMPF.  Give up on this presidential election.  You’ve already lost it, but at the least you can save your party.  It is not too late.  Save yourselves from the idiots.   Though I know your party has a lot of them, they are not a majority (yet).

Monday, March 07, 2016

Discussions on Wealth (part 13): Chapter 6: summary part 2 and discussion

This discussion on wealth is an offshoot of  Serious Conversations parts 53 and 54.  We are considering the book  The Origin of Wealth by Eric D. Beinhocker.  (I do not profit from clicks).  (Ed.:  we will be taking the general format of outlining the major points of the chapter and then discussing what we believe to be important or intriguing points.)

Last time we covered the new theory of bounded rationality which says while humans are smart, we aren’t that smart.  This is unlike traditional economics where humans a (laughably) perfectly rational.  Most importantly we have the process of inductive reasoning described.  The example of a frog is used to demonstrate how agents would use rules and inputs to determine behavior.  For example, IF [small] , [flying] THEN [extend tongue].  

We conclude the Ch 6 discussion by considering how this inductive model could be applied to describe the stock market.  A new model like Sugar-scape but applying the frog model is used to model the stock market.  The important change is that the stock market agents can learn.  A market with one stock and a random dividend was created; the sole goal of 100 agents was to make money.  The 100 agents each had 100 rules of varying complexity that determined when they would buy and sell.  Like the frog example, the agents decide on which rule by what has worked in the past.  The process of learning was introduced by randomly removing poorly performing rules and making new ones by randomly concatenating old rules that worked.  A test case with one rule that was of perfect rationality showed that there was little volatility and everyone made pretty much the same amount of money.  This is the situation predicted by Traditional economics.  The second run utilized the full strategy above.  Trading volume and volatility went up.  The stock price varied dramatically.  Some agents did very well, others went bankrupt.  It essentially duplicated the real world.  


I’d like to use the ultimatum game to talk about income inequality.  It really is shocking to me that the income inequality gap isn’t a bigger deal in society today.  So few have so much, while the rest of us have so little.  I would think that we would be okay with the economy slowing some so that the super rich don’t keep gaining on us.  I know I would be, even it was to our short term detriment.  I’m also so surprised that the poor in the deep south are some of the most ingrained into the conservative economic model or trickle down economics, which clearly doesn’t work.  Many of them are against raising the minimum wage when most would benefit.  It is amazing that the GOP has convinced these people to vote against their economic interest just because they share social interests. 

Friday, February 12, 2016

Discussions on Wealth (part 12): Chapter 6: summary part 1

This discussion on wealth is an offshoot of  Serious Conversations parts 53 and 54.  We are considering the book  The Origin of Wealth by Eric D. Beinhocker.  (I do not profit from clicks).  (Ed.:  we will be taking the general format of outlining the major points of the chapter and then discussing what we believe to be important or intriguing points.)

This Chapter is about how economics views humans.  We are finally addressing the ridiculous proposition of the completely rational human.  We begin with the absurdity that Traditional economics thinks each human goes through when it considers a purchase.  We should, according to Traditional theory, consider the purchase of any item in the context of all possible future items we might need with a logical plan about how purchases effect our budget and with logical consistent preferences.  Also considered how that money spent on the purchase will effect all future decisions.  Complexity economics recognizes that humans are impulsive and might buy something on a whim.  We are introduced to a new theory, bounded rationality, which says while humans are smart, we aren’t that smart.  We have imperfect computing capability and imperfect information.  We “take the information we have, and we do the best we can.”  Finally, behavioral economics is noted that shows people do not follow the Traditional economics paradigm of human behavior, but there is no way to model it.

As an example of irrationality we have been given a version of the ultimatum game.  Traditional economics says that any offer should be accepted by the second participant because whatever the amount they are still richer for it.  This does not happen because humans are programed with a degree of fairness as a result of our evolution.  We each feel it our duty to hold other accountable.  

Another flaw of Traditional economics is that humans never make mistakes.  A series of common biases which lead to mistakes is described:  framing bias, representativeness, availability biases, difficulties judging risk, superstitious reasoning, mental accounting.  A perfectly rational human could not take advantage of other’s biases because it is impossible to build a perfectly rational machine.

Inductive (reasoning by pattern recognition) and deductive (reasoning using logic) reasoning are contrasted.  Traditional theory considers humans perfectly deductive when we are certainly not.  We reasoning by induction, using past experience to influence decision making.  An inductive model is described as an agent that has a set of goals and a way to determine if its decisions bring it closer or further from those goals.  A list of condition-action rules (if-then statements) dictate the course of action.  The agent can add to the list of rules based on experience.  If an action has deleterious consequences it is applied less frequently.  This model is explained by way of a frog.  It has simple actions including [flee], [pursue], [extend tongue], etc.  It has various inputs [moving], [striped], [near], [blue], etc.  And various rules IF [small], [flying] THEN [extend tongue].  These rules can be changed; however, if the rules are ever in conflict the frog has credit assignment where rules are scored based on past helpfulness.  The higher scored rule is more frequently used.  This simple model can also be used to plan out long term goals using a market system.  Rules compete with each other by bidding using their credit.  Finally we assume that the rules self-organize into hierarchies.  Rules become associated with each other (e.g. [large], [flying], [flapping] are associated with [bird]).  This allows the system to respond to new situations and allows for reasoning by analogy.  

Friday, January 22, 2016

Serious conversations (part 67): What is science - part 5

This series is a continuation of my conversations with an atheist friend of mine.  These are my edited responses from that conversation.  The sixty-third – sixty-ninth entries deal with the nature of science.

Part five continues what part four started by exploring examples of who is a scientist.

Is a lab tech a scientist?  If a tech is merely acting as a sophisticated machine, they cannot be a scientist.  Transferring samples from one place to another or pushing some buttons does not make one a scientist, but performing moderately complex tasks does.  I almost think I would have to be given examples of mundane lab tasks and explain each as science or not.  I’m not sure I can put into words a concise, general rule for if a task is science.  Following a rote procedure that is laid out is not contributing to science, but at some point even repetitive tasks with clearly defined procedures become science-like if they are complicated enough.  Perhaps I should say that repetitive tasks become science if they require independent thought and adaptability outside of established guidelines to perform.  But then I get the question how complex does a machine have to be where operating it becomes science in and of itself.  The techs in the control room of the LHC are scientists, right?  Or no?  I’m not sure.  Experimentation is the key; is the person developing the experiment and changing the methods based off of the observations or are they merely the tools others use to perform the experiment?  If they are the ones actively adapting their methodology according to observation then they are a scientist; if not, they are merely part of the instrumentation. 

The complexity of science almost requires teams of people – a primary scientist with helpers around them that are quasi-scientists that contribute to the endeavor.  Are students of science scientists?  I would argue that grad students are scientists because even though they are doing the grunt work of a tech, they do it with the goal of learning.  And as I’ve said before, those who are performing their own personal science are still scientists.  They are learning the process of science, which I would call science.  I would argue that even the grunt undergrad laborer is also a scientist because of their intentions.  They are attempting to expand their own knowledge.  This is distinct from a lab worker who might only be working for the pay.  This leads me to speculate on levels of a scientist.  We sort of do it already.  A professor or research scientist at a government lab or private enterprise is at the top, followed by associate scientists/professors and so on, then post-docs, grad students, undergrads.  The professor is more of a scientist than an undergrad (within the same field).  This will lead us to part six.
2003-2016 Michael Battalio (michael[at]battalio.com)