Andereggetal said:Furthermore, the vast majority of comments pertain to how the study could have been done differently. To the authors of such comments, we offer two words do so! Thats the hallmark of science.
You did not answer the question, as it directly applies to the flawed methods used by Anderegg et al.This is called "filtering", PopTech. As I said, I am often published under my first two initials. In fact it is not that uncommon. However if one wishes to ensure they will capture UNRELATED hits on names similar to mine they may wish to drop my second initial. My last name isn't all that common, but you should get the point.
An accurate count is absolutely critical. Erroneous data is not "noise" but evidence that Google Scholar cannot be used for this type of study, since it is merely a "scholarly" search engine that does not use robust methods to obtain search results. The only reliable way to use Google Scholar in such a study is to verify every single result, something Anderegg et al. did not do.You know as well as I do that the absolute count is not absolutely critical. There is noise in the data as part of the weakness of ANY database. Databases as you have noted are dynamic and often sloppy. Noise.
It is irrelevant if they tested it for "robustness", they are explicitly making the claim that someone who publishes at the 20 paper threshold is an "expert" and anyone else is not.I have already addressed this. Do not make yourself out to be a LIAR (as you like to accuse everyone else).
Expertise is subjective and Anderegg et al. at least went so far as to establish a baseline for their study and tested the robustness of this.
11. Is the data used by Anderegg et al. reliable and reproducible?It shows that no matter how the data is parsed those with a baseline history of publication and research in the field are OVERWHELMINGLY more likely to be in the CE category than UE category. Buy such a large margin that if it were otherwise the p-value would be much, much higher.
Why would I be interested in if a paper was popular or not? How can that tell me if a paper is scientifically valid?And again, it would be trivial for folks like YOU to actually do not just a "count" analysis, but a CITATION analysis and find an absolutely different result. But you don't. Why is that? Because you can't.
I am not talking about Anderegg et al. here. My question was in response to your argument that citation count implies scientific validity,And that is flawed on many vectors:
1. A single search is NOT what Anderegg et al were doing.
2. You are looking at a raw count on one search
3. This has nothing to do with the TYPE of analysis Anderegg et al were doing. (ie it is not a credibility or citation analysis.)
The data and methods used by Anderegg et al. are unreliable and thus no meaningful statistical analysis is possible.I await YOUR response to the challenge set out to you do an actual analysis showing that the UE group is so vast and so well published in the climate sciences that there is almost no STATISTICAL DIFFERENCE in the populations as expressed in Anderegg et al.
Citation counts cannot determine consensus, all they can tell you is popularity.Now, if you wish to say that there is NO OBJECTIVE WAY to determine a "consensus" in a field then fine! But that is kind of silly since there is. And an analysis of citations will do that.
This is unsubstantiated conjecture. Please provide the objective criteria for determining who is a "climate scientist". The CE group in Anderegg et al. is very specific to those willing to sign a statement in support of political action in response to belief in AGW. This will be quite different from scientists who may accept an anthropogenic component to climate change but differ on degree and/or policy recommendations. Conflating these groups together would be unwise.But it is like missing the forest for the trees. Meanwhile nearly every single climate scientist you will meet (assuming you get out of the skeptic blogger bubble you appear to live in) will probably fall in the "CE" category. There's a 97% likelihood of that.
I have no interest in getting published and have made no attempt to. This does not change the fact that I am very familiar with the process.So keep on "assisting" people who get published. Maybe you'll get published one day.
I don't need to publish in any journal to show this, as it is clearly demonstrated on my website. No one with a background in computer science ever argues with me about my Google Scholar critiques, they either immediately accept them or concede - as the arguments are irrefutable since we are dealing with how the software works not the fantasy land of those like yourself that don't. That speaks volumes to my credibility on this issue. Also whenever this is discussed in forums no one with any computer background EVER comes into to embarrass themselves in these debates because they know better and cannot help people like you.If your "Expertise" is so solid in this world of "LIARS" and "COMPUTER ILLITERATES" then by all means: DO YOUR OWN ANALYSIS and RUN THE NUMBERS.
Show the world they are LIARS and ILLITERATES.
Why are you so desperate to smear me with this dishonest ad hominem?That's why Creationists do what they do.
There is no clear picture in statistics derived from flawed data. I am claiming that the conclusions of Anderegg et al. are worthless because they are based on flawed data and methods.PopTech has missed the greater picture clearly visible in the statistics. He is claiming that the SELECTION methods of Anderegg et al. are so bad that it calls into question the idea that there is a solid scientific consensus on the topic.
Since when is someone after demonstrating a study's conclusion is worthless required to do their own study? I consider the level of "consensus" on this issue unknown.If PopTech is only interested in tossing the 97% figure then will he be OK if HIS analysis shows a 90% figure? Or how about 86%?
Nope, I am discrediting the flawed studies you are trying to use to support your "consensus" argument.But PopTech is mongering doubt.
You do not consider these types of errors horrific?He has failed to appreciate the power of statistical analysis. Even if the values of Anderegg et al's searches were different due to poor search criteria etc. they would have to be EXTRAORDINARILY off the mark to result in such horrific errors that PopTech seems to see.
Not at all and I am well aware it is arbitrary. I am asking her a specific question relating to the methods used in Anderegg et al.,Are you guys seriously arguing about the citation style in scientific publications? It's really arbitrary, but most common is last name comma first initial(s), middle name initial.
An accurate count is absolutely critical.
Erroneous data is not "noise" but evidence that Google Scholar cannot be used for this type of study
With bibliographic databases like Scopus and Web of Science you will not see massive negative "corrections" like you do with Google Scholar. Instead you would likely see an increase as these authors publish more or at best the numbers staying the same.
I am not sure why you are trying to dismiss this evidence - instead of being intellectually honest. As an example,
I will rephrase the questions,
7. Do you consider a scientist who has published 20 peer-reviewed papers on climate change should be considered an expert and someone who published only 19 not?
Why would I be interested in if a paper was popular or not? How can that tell me if a paper is scientifically valid?
I am not talking about Anderegg et al. here. My question was in response to your argument that citation count implies scientific validity,
10. Is "Intelligent design: The bridge between science & theology" scientifically valid because it is cited 353 times?
The data and methods used by Anderegg et al. are unreliable and thus no meaningful statistical analysis is possible.
Citation counts cannot determine consensus, all they can tell you is popularity.
I have no interest in getting published and have made no attempt to.
This does not change the fact that I am very familiar with the process.
No one with a background in computer science ever argues with me about my Google Scholar critiques
, they either immediately accept them or concede - as the arguments are irrefutable
That speaks volumes to my credibility on this issue.
Why are you so desperate to smear me with this dishonest ad hominem?
Furthermore, the vast majority of comments pertain to how the study could have been done differently. To the authors of such comments, we offer two words – do so! That’s the hallmark of science.(HERE)
Since when is someone after demonstrating a study's conclusion is worthless required to do their own study?
I consider the level of "consensus" on this issue unknown.
Strawman, my critiques of Anderegg et al. have to do with flawed methods and erroneous data not the representativeness of the sample.So when you said you had statistical training, did you miss the whole "sample vs population" lecture? ...but the idea of a sample is that it is not a PERFECT mirror of the population. Hence there is ERROR associated with the measure.
Accurate as in, does not include unreliable and erroneous data. A meaningful statistical analysis cannot be done on unreliable and erroneous data. Using your logic I could create "Poptech's scholarly database" that was full of unreliable and erroneous data but so long as I ran a "statistical analysis" on the data my conclusions would always be valid.A count should be accurate, yes, but that is why Anderegg et al. ran a statistical analysis!
The existence of the Internet invalidates the argument of a geographic location as an impediment. It is reasonable to suggest that with the existence of the Internet and the IPCC, these scientists are more likely to know each other than not. Anderegg et al. even conceded that they were unable to rule out self-citation and clique citation bias,Now let us assume that NOT ALL 908 people in the study KNOW EACH OTHER PERSONALLY and rub each other's necks at the "office party" and rather view the REALITY that this amounts to nearly 1000 individual people spread ALL OVER THE EARTH.
Like I pointed out earlier, WHEN MY PAPERS ARE CITED it is often by people I DON"T EVEN KNOW EXIST. So how could I impact my citation analysis in those instances?
This is an argumentum ad populum logical fallacy, as "prominence" does not equal scientific validity.It couldn't be more fair than that! AND it is not limited to their "climate only" work! They just want to figure out how "Prominent" they are in the scientific community!
No all inclusive database exists to present a methodology that would not be biased.SO WHAT METHODOLOGY WOULD YOU USE?
I simply used Scopus as an example of a bibliographic database that you would not see massive negative "corrections" like you do with Google Scholar. I do not have to do my own analysis to prove that Anderegg et al.'s is worthless.Then do your analysis using Scopus.
Honestly! I mean, seriously! Anderegg et al. stated explicitly all the limitations of their study and they have asked that critics such as yourself DO YOUR OWN ANALYSIS!
This is a dishonest ad hominem and a dishonest circumstantial ad hominem.This is why I say you are arguing like a creationist. You are mongering doubt for doubt's sake
This is false, if they understood the limitations of using Google Scholar they would of never used it for their study.Because Anderegg et al. explicitly state all the limitations of their analysis and within the bounds of the analysis it is STATISTICALLY ROBUST.
I have seen no such evidence to draw any such conclusions, Doran and Zimmerman (2009) suffers from a biased sample of only 75 scientists.And when you compare this to other studies such as Dornan et al (EOS) and other self-reporting type analyses you see the vast majority of climate researchers are "convinced" by the evidence.
I am not confused at all, as there is no way to objectively determine the motives for which a paper is cited.You are so desperately confused by what "popular" means in science. Science cites papers not based on popularity as you may know it from high school, but on whether the data and conclusions are worthy of citation or further testing. [...] I would like to point out that citations don't always mean the author "likes" the study they are citing. I had one study of mine in which I was cited so that the researcher citing me could point out an error I made.
Strawman - again, you failed to grasp my argument. I am not talking about Anderegg et al. but your argument that citation count implies scientific validity,And again, you fail to grasp the point of the article.
This is again a dishonest ad hominem.Well, if you are NOT like a creationist in debating style
Strawman, I never claimed it was.Clearly it was not your own research as you only "assisted" and were not a co-author.
Which lecture in statistics tells you how sampling solves the problem of unreliable and erroneous data?Sampling. You must have missed that lecture in your statistics training.
Again, why has no one with a computer science background challenged my arguments about the limitations of Google Scholar for these types of studies? My critiques of their improper use of Google Scholar will certainly make computer literate people wary of citing Anderegg et al. to support a consensus argument.Your "credibility", such as it is, is limited to "blogging". Versus the science which is pretty solid and almost every metric by which one can assess the "consensus", there is almost no way in which your "critiques" of the Google Scholar search will change the raw fact that nearly every climate researcher on the planet is in the CE group.
What are you talking about? What sampling?YOUR sampling, however, is of a limited number of skeptics and fellow bloggers with almost no CLIMATE RELEVANT expertise or training.
So you admit to trying to smear me with dishonest ad hominems based on falsely implied motives?Because that is how you are debating.
You are casting doubt (and NEVER conduct an analysis of your own...you merely pick apart and find areas to "question", but never answer any questions yourself).
More dishonest ad hominems.THAT is why. All I would need to do is change a couple nouns in your screeds to something related to "Genesis" and I'd have a carbon copy of most creation vs evolution debates.
No I am focusing on your flawed consensus argument. You were the one that foolishly attempted to use Anderegg et al. to support a flawed consensus argument.You are ignoring the science of AGW to focus on a sideshow, and even doing that you never actually do a contrasting analysis to show how the numbers really look.
You argue like a Nazi propaganda minister. I have no idea how you received a Ph.D.In creationist-type circles: NEVER!
I talk to climate researchers on a weekly basis and they do not support your position.Of course you do! It is "doubt"! And that's all that counts!
Unless, of course, you actually talk to climate researchers and hang around the world's top earth science research facilities (as I have been lucky enough to occasionally do). Only then do you realize that the "doubt" you wish to live with really isn't that doubtful.
Which lecture in statistics tells you how sampling solves the problem of unreliable and erroneous data?
Again, why has no one with a computer science background challenged my arguments about the limitations of Google Scholar
for these types of studies? My critiques of their improper use of Google Scholar will certainly make computer literate people wary of citing Anderegg et al. to support a consensus argument.
You have polled every climate researcher on the planet?
What are you talking about? What sampling?
Please provide the objective criteria for determining if someone has "climate relevant" expertise or training.
So you admit to trying to smear me with dishonest ad hominems based on falsely implied motives?
More dishonest ad hominems.
No I am focusing on your flawed consensus argument. You were the one that foolishly attempted to use Anderegg et al. to support a flawed consensus argument.
I do not have to do my own analysis to prove that Anderegg et al.'s is worthless.
You argue like a Nazi propaganda minister. I have no idea how you received a Ph.D.
Intellectual honesty is all that counts which is why I honestly state that,
I consider the level of "consensus" on this issue unknown.
Accurate as in, does not include unreliable and erroneous data. A meaningful statistical analysis cannot be done on unreliable and erroneous data. Using your logic I could create "Poptech's scholarly database" that was full of unreliable and erroneous data but so long as I ran a "statistical analysis" on the data my conclusions would always be valid.
...
11. Is the data used by Anderegg et al. reliable and reproducible?[/COLOR][/B]
In that any sample is "reproducible" from an unknown population, yeah.
No all inclusive database exists to present a methodology that would not be biased.
Now you have found BIAS??? What kind of statistical analysis did you use to come to THAT conclusion?
But really, HOW DO YOU KNOW THIS? In fact, ANY database can be thus analyzed. Unless Anderegg went to the "We Hate Denialists" Publication Database there is no reasonable reason NOT to analyze Google Scholar.
But again, Scopus would be a good one. I'd like to see your similar analysis of Scopus (which I know you won't do...that's called actual research, rather than "critique".)
I simply used Scopus as an example of a bibliographic database that you would not see massive negative "corrections" like you do with Google Scholar. I do not have to do my own analysis to prove that Anderegg et al.'s is worthless.
Again, you actually DO have to do an analysis. Or you have to show mathematically how ANY GIVEN DATABASE SAMPLING will yield a non-robust response.
That's the only way the game can be played.
Oh, and please don't confuse your anecdotal "I got x hits for Phil Jones and they got y" type argument. It goes much more in-depth than that! That's anecdotal data and has no place in statistics.
(Again, if you don't have a handy stats package like JMP or SPSS or Minitab, you can download R for free! It's a no-brainer for a computer scientist like yourself...it's command line! Hardcore stuff that computer illiterates like myself simply can't do!)
All I see for the coming seasons is global cooling.
Can't wait til the June satellite data comes out
,more cooling coming. Yes I will have the last laugh this Winter when there is no stopping the cooling from rising above the noise so everyone will see it, brrrrrrrr keep your coat handy.
Lucy, continues to dodge my questions (re-numbering them here) and instead argue strawman arguments,
5. Are 17% (120) of the results used for Phil Jones erroneous?
6. Are 51% (290) of the results used for Andrew J Weaver erroneous?
8. Is a scientist who has published 19 peer-reviewed papers on climate change an expert?
9. Is "Intelligent design: The bridge between science & theology" scientifically valid because it is cited 353 times?
[/COLOR][/B]
Strawman, that is not the questions I asked,I showed you, explicitly, in the post above, that CHANGING EVERY COUNT DOWN BY 25% doesn't change the results from the "example" I gave.
So how would 17% change IN ONE AUTHOR'S COUNT affect the results???
This is not what I asked you,This is arbitrarily established as a "cutoff filter". But again, YOU could run your own analysis.
But then you wouldn't be doing the same type of research. Because there are people who can get maybe one publication in a field WHO ARE NOT CAPABLE RESEARCHERS, certainly not EXPERT.
Strawman argument for the third time,THis is your funniest question because it really has NO BEARING ON THIS TYPE OF STUDY.
Do you even understand what Anderegg et al were doing? Because when you ask this question you make it clear you really don't.
A meaningful statistical analysis cannot be done on bad data.
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