Speaking as someone with formal statistical qualifications who does text mining / natural language processing for a living, this sort of thing really isn't too terribly exciting.

Let's suppose we want to reverse engineer Mr. High - setting up scrapers isn't too terribly challenging, maybe you just eat a bunch of RSS feeds and call it a day. From there, you can apply a great many pre-trained models for sentiment, emotion, or the WordNet emotional ontology. After that, you have some results, say you decide to plot them - let's say you look at the emotional rate of change, or emerging clusters around a topic, so on and so forth. A competent Python programmer could have a working proof of concept in hours.

The burning questions are then 1) how do you know you haven't stumbled on random noise in your data mining and 2) how do you know that you haven't goofed up by doing ersatz channeling as data mining by yourself?

To the contrary, this sort of data mining is simply unvalidated data exploration. Gotta have the validation step - isn't that part of why we're on this research forum?
I hesitated mentioning this aspect since I'm no techie myself, and since I knew I could only describe High's process in a greatly reduced way. You'd have to dig around for how he describes what he's done. Don't rely on my version (!). Then you can draw a better conclusion. Perhaps you'd still be unimpressed, but at least you are getting a more accurate understanding of what you are unimpressed by!
 
Speaking as someone with formal statistical qualifications who does text mining / natural language processing for a living, this sort of thing really isn't too terribly exciting.

Let's suppose we want to reverse engineer Mr. High - setting up scrapers isn't too terribly challenging, maybe you just eat a bunch of RSS feeds and call it a day. From there, you can apply a great many pre-trained models for sentiment, emotion, or the WordNet emotional ontology. After that, you have some results, say you decide to plot them - let's say you look at the emotional rate of change, or emerging clusters around a topic, so on and so forth. A competent Python programmer could have a working proof of concept in hours.

The burning questions are then 1) how do you know you haven't stumbled on random noise in your data mining and 2) how do you know that you haven't goofed up by doing ersatz channeling as data mining by yourself?

To the contrary, this sort of data mining is simply unvalidated data exploration. Gotta have the validation step - isn't that part of why we're on this research forum?
For question 1 I would say that normally one would expect random noise in any data set, otherwise, building and tuning accurate models would not be so difficult. I think Clif is in danger of 'fooling himself', I suspect he's not well networked - which addresses question 2.

I find his basic idea interesting, however - being able to get useful info by aggregating text from many different sources, and creating data structures that can be gainfully analyzed via a predictive algorithm that measures sentiment and emotion.

A good programmer could quickly come up with a workflow similar to what you described - but cleaning and structuring the data would be an ongoing process. And due to the nature of what is being studied, interpreting the data would take years, as would tuning and re-feature engineering after much constant testing on new data. Clif has been working on this for years. The algorithms he uses are probably his own. I doubt he is going to cough up any source code for independent analysis, I wonder why isn't he more open with his methods and findings if he has anything worthwhile.

He seems authentic and he has some interesting and sundry ideas other than what he gets from his data sets. However, perspicacity in regard to Clif High - and everything else on the Interwebs these days.
 
For question 1 I would say that normally one would expect random noise in any data set, otherwise, building and tuning accurate models would not be so difficult. I think Clif is in danger of 'fooling himself', I suspect he's not well networked - which addresses question 2.

I find his basic idea interesting, however - being able to get useful info by aggregating text from many different sources, and creating data structures that can be gainfully analyzed via a predictive algorithm that measures sentiment and emotion.

A good programmer could quickly come up with a workflow similar to what you described - but cleaning and structuring the data would be an ongoing process. And due to the nature of what is being studied, interpreting the data would take years, as would tuning and re-feature engineering after much constant testing on new data. Clif has been working on this for years. The algorithms he uses are probably his own. I doubt he is going to cough up any source code for independent analysis, I wonder why isn't he more open with his methods and findings if he has anything worthwhile.

He seems authentic and he has some interesting and sundry ideas other than what he gets from his data sets. However, perspicacity in regard to Clif High - and everything else on the Interwebs these days.
(bold and italic from me)
cleaning and structuring the data from what point/perspective? Isn't that the point? Just have a look on the raw data. that is enough. no clearing and structuring needed. And you say it would take years to interpret the data... no, why? It can be done quite quickly, as for example a german guy demonstrated just recently. [
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Canada situation worsen (translated from French)

New measures for public places

In addition, the province is implementing new restrictions for indoor public places starting Thursday. In addition to mandatory masking, physical distancing will be required.

For those vaccinated, all private indoor gatherings will be limited to 10 people from no more than two households. There will be no limit for children under the age of 12.

People living alone will be allowed, as at the start of the pandemic, to have two named contacts, provided that all are vaccinated.

Unvaccinated persons over 12 years of age will not be allowed to attend any private indoor gathering

L’Alberta restreint les activités des personnes non vaccinées | Coronavirus

[Edit]
Found an English source:
  • Working from home will be mandatory unless an employer determines a physical presence is required.
  • Indoor private gatherings for fully vaccinated individuals are limited to a single household, plus one other household, to a maximum of 10 people. There are no restrictions on children under the age of 12.
  • Eligible people who are unvaccinated are not permitted to attend any indoor private social gathering.
  • Outdoor private social gatherings are limited to a maximum of 200 people, with two-metre distancing maintained at all times.
  • Places of worship must limit attendance to one-third of fire code capacity. Face masks will be mandatory and physical distancing will be required between households.
  • No attendance restrictions on outdoor events and facilities, but two-metre physical distancing must be in place.
  • Schools will be required to have mandatory masking for students in Grade 4 and up, plus staff and teachers in all grades. Exemptions will be available for schools with alternate safety plans.
  • Indoor children's sport and recreation activities are permitted, with requirements for physical distancing and masking where possible.

 
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A good programmer could quickly come up with a workflow similar to what you described - but cleaning and structuring the data would be an ongoing process. And due to the nature of what is being studied, interpreting the data would take years, as would tuning and re-feature engineering after much constant testing on new data. Clif has been working on this for years. The algorithms he uses are probably his own. I doubt he is going to cough up any source code for independent analysis, I wonder why isn't he more open with his methods and findings if he has anything worthwhile.

I've been wondering about this myself. Down-to-earth considerations aside, i think Clif may be unwilling to share his software partly because he ended up with a system that is very "personalized" in that it produces an output that serves to facilitate his innate intuitive capabilities, more than anything else. Others simply wouldn't be able to make much sense of the data Clif obtains. If that's indeed the case, his project should be considered an advanced divination scheme, of a more lucid kind perhaps.

I can't help feeling sympathy for Clif as a person and listening to his Woo-talks, even though i've noticed he repeatedly gets details wrong and doesn't always verify his information. He has his moments of genius but also ones in which he comes up a bit like unsecure mythomaniac. Always inspiring & thought-provoking, though.
 
(bold and italic from me)
cleaning and structuring the data from what point/perspective? Isn't that the point? Just have a look on the raw data. that is enough. no clearing and structuring needed. And you say it would take years to interpret the data... no, why? It can be done quite quickly, as for example a german guy demonstrated just recently. [
]
Text is known to be difficult to structure. Numerical data is probably the easiest. Remember that this involves scraping text from a number of sources. Many sites do many different things. Text formatting, missing fields, language, etc. come into play. Additional difficulties arise when attempting to predict human behavior. Sure, it's not hard to get a lot of info from raw data. But that doesn't mean it's not worthwhile to scale, restructure, impute, or otherwise engineer data for better predictions or to focus on certain specific data that answers the unique goals of the analysis. Much depends on what is being studied and how the alternative and null hypotheses are formed.

So good for the analyst, he found some raw data source(s) about covid that he could explore right off the bat, but depending on the questions asked, a good deal of additional work may, or may not be called for. It depends.
 
Well, I will endure any pressure or threaten from STS forces, even death. And just focus in my chosen path to graduate this Grand Cycle, and determined to mover into next higher density.

December 3, 1994

Q: (L) Well, why is all this activity happening now?

A: The grand cycle is about to close presenting a unique opportunity.

Q: (L) Does this mean that this is a unique opportunity to change the future?

A: Future, past and present.

Q: (L) When was the last time a realm border crossed as far as the earth is concerned?

A: As you measure, on Earth, 309,000 years ago.

January 11, 1997

Q: (Laura) Well, the bad thing about it is, I'm even wondering if they mean totally eliminated in physical terms, because what they are really trying to do is to get a person, even if it's under deception, to make a choice for their side, so that they can accrue their energy. I mean, it's like the currency, each person they collect to, you know, go with their propaganda, becomes a soul in their pocket... so to speak.

And J, I'd have to say, is perilously close to making that choice. Because he is so firmly into the 3rd density reality. I mean, he can't even let go of the Nephilim, and the Annunaki being on the planet Nibiru, and being strictly physical overlords and masters, that evolved, and blah blah blah. (Terry) Well, they aren't going to leave him here when they... (Laura) Is this the primary issue here; that it is really a war for souls?

A: Best way to get souls is to remove bodies.

Q: (Laura) So, if they get souls... (Terry) Is J dealing with somebody he should be really careful of?

A: Quite a few, actually.

Q: (Terry) Is it still on the level of the in-your-face attack?

A: All sorts.

Q: (Terry) What does J need to do? (Laura) Well, they're not going to tell you that...

A: Purge and begin anew.

January 30th 2021

(Joe) The COVID thing is obviously directly related to losing control.

(L) COVID is all about losing control.

A: Yes

Q: (L) And they use COVID for just about anything they want to.

A: Yes

(Joe) In all the vaccines they're releasing for Covid, is there any chipping, or...?

(Niall) They answered that. They suggested it themselves without us asking.

(Joe) Well, that was back then. Are there chips in any of the vaccines they're administering?

A: Yes

Q: (Joe) Which ones? Pfizer?

A: Selective and specific.

Q: (Joe) And what is the purpose of these chips that are administered selectively?

A: Control.

Q: (Joe) Control of individuals?

A: Yes

Q: (Joe) What kind of control can they affect with those?

A: Tracking and other.

Q: (Joe) Can they have an influence on people's thoughts and behavior?

A: Not thoughts, but physiology.

Q: (L) So they don't need something like that for controlling thoughts. They've got other things for that. But they could probably put something in there that could trigger something that would go off in your body and like create an illness, or...

(Joe) Is that being done for experimentation purposes to do it on more people at a later point?

A: No. Raw control.

Q: (L) No experimenting necessary. They've already done that.

(Andromeda) Are they chips like we think of them, like computer chips? Or is it a higher technology?

A: Nano.

Q: (Joe) Is there anything specific about the people they select, or is it random?

A: Difficult to control.

Q: (L) Obviously, somebody who's easy to control would just, ya know...

(Joe) But then my next question is how do they decide who needs it...

(Niall) Maybe it depends on what they say on Facebook? Those who are dissident get targeted for a chip.

A: Knowledge protects. Review what you have learned about "alien" implants.

Q: (Pierre) But then the most uncontrollable ones won't get the vaccine. They'll refuse it.

A: True. Wishful thinking.

Q: (L) So it's wishful thinking on their part that they think they can get any uncontrollable people controlled?

A: Yes

Q: (Pierre) They will control the individuals that are already sheep.

A: Yes

Q: (L) Okay. Any other questions?

(Artemis) Who created this nanotech? Humans or aliens or inspired by aliens?

A: Both.
 
In Switzerland it was decided from Monday the 13th of September a QR code was needed to go to restaurants, museums etc. The 3 ways to get a QR code was 1) tested (Getested) 2) vaccinated (Geimpft) and 3) having had it within 6 months (Genesen). So it is called the 3Gs, which is why I put the German word in brackets for better understanding where the 3G came from.

Ysus and I both had Covid, but that was already 7 months ago, so no QR code possible. In order to be a little prepared when confronted with vacced people, we decided to go to a lab yesterday to have a serum antibody test, which is an actual blood test where the number of antibodies per unit is listed.

The results came today and they were interesting though there was only a very rudimentary explanation of what the results mean.
My results can be seen below:
View attachment 49460
[The values are according to WHO standards and the values on right means: negative, borderline, weak positive, positive and strongly positive]

From the above I got the idea that I have a fairly strong antibody response as it is much higher than just positive. That there is a red exclamation mark and that the value is also in red just highlight this fact. It even made me wonder if I currently have a renewed asymptomatic infection that my immune system is fine handling by itself without telling me about it ;) A few days ago, I did have a slight tickle in the throat in the evening and the following morning, but that was all.

The test for my wife came out negative with a value of just 0.69.

The internet did not provide much information on how to interpret the data which is understandable as they don't recognise such a test anyway. That would be contrary to the push for the vaccine and as we know this was never about health in the first place.

Has anybody else taken such a test as the one above?
Both my sister and my brother in law had covid. My brother in law ended up in the hospital. After his recovery, both went to test for antibodies. My sister had under 10 and my brother in law 450. Here is where I hope the relevance of my answer is not purely anecdotical, as my sister was furious as to why should she have so few antibodies and her husband so many? In her opinion it was just not fair to have only 3.
Back to the results you mentioned, I think they pick up also, a possible initial viral load in the brackets. It is interesting to find out the type of the test administered, as I have been told there are two antibody related post covid tests. For the fact that your results are high, could just indicate that you might have had or accumulated a very big viral load.
 
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@Tuulikki

Have you been dismissed from your job yet?


On the eve of the deadline for carers to get their first jab, the Department of Health has issued guidance that carers can self-certify that they have a medical exemption which gets them out of it.Exemptions include: terminal illness, a learning difficulty, autism or allergy to vaccine.

The exemptions will be temporary, but essentially a carer can now self-declare that they shouldn’t have to have the jab.

Here's the self exemption form

 
@SOTTREADER

No I haven't been dismissed until the actual date I have to leave, which is the 11th November. This is in common with all the other carers in the country who have not been vaccinated. I read the article you posted about the temporary exemptions from the vaccination with interest. I have tried this route because the exemptions were mentioned in my pre-dismissal letter from the company I work for. However, they have tightened the loop a little. Originally the exemptions included serious allergies (I do suffer from a serious allergy to certain nuts).
The new information however said that you needed to be allergic to one of the ingredients of the vaccine to qualify for exemption.

I am a patient of one of the most pro-vaccination health centres in the entire country...I think. My own GP is brilliant in every way but is totally on board with the covid 19 vaccinations and she knows my medical history very well as I have been a patient for practically my entire adult life. I realise this is a self-certification system but there would probably be some recourse to the health centre being informed at some stage.

I think this is a temporary fix for a serious and chronic problem. The social care sector has been short of staff for years due to very hard work, unsocial hours and lack of a decent salary. It seems to me the government is giving themselves some thinking time to try and sort out the problem. The actual criteria mentioned is also interesting. The numbers of staff who could claim to have a terminal illness must be very tiny and would have to be upheld by their GP. Autism seems a tricky one as it would be a very difficult job to hold down if you were suffering from this condition and your colleagues and employers would presumably be aware. Learning difficulties is quite wide ranging. We have a number of staff at present in my residential home who are diagnosed as having mild learning difficulties. Again, colleagues and employers would be aware of who these people were. That leaves allergies. This is the most wide ranging of all. Allergies can crop up spontaneously in late adulthood - as did my allergies to certain nuts. However it seems they will only accept proven, dianosed allergies to the vaccine ingredients. PEG allergies have been mentioned quite a lot.

If this is a government designed temporary lifeline in order not to have a huge exodus from the care section in early November, it doesn't seem as if it will be very successful. The criteria seem to be too narrow for very much manoeuvre.

The article says:

The exemptions will be temporary, but essentially a carer can now self-declare that they shouldn’t have to have the jab. How on earth care homes will verify that claim is unclear. Exemptions will only last until an “NHS Covid Pass system” is launched - date TBC.

I cannot even guess as to how many affected staff will take up this offer. I think the government are clutching at straws here. In three months time the same situation will arise so it is just putting off the inevitable. Perhaps they are hoping that certain events will occur which will sort out the problem permanently i.e. massive numbers of deaths in care homes due to weakened immune systems which leave the residents open to serious and life threatening infections. This would thereby reduce the number of staff needed to work in the homes.

It will be interesting to see how this plays out.
 
Still no official data for my country, but I managed to find data for one county. They just started to release this data but I wonder how long will this be permitted.
And just like I predicted, today they stopped giving the information about the number of unvaccinated and vaccinated people who ended up in hospitals. Here is the last info:

16.09.2021.

The admission of 82 people was recorded, while 38 were released.

58 unvaccinated patients were admitted for treatment, 21 people were admitted with both doses of Sinofarm, two with Pfizer and one patient with Sputnik.
 
Text is known to be difficult to structure. Numerical data is probably the easiest. Remember that this involves scraping text from a number of sources. Many sites do many different things. Text formatting, missing fields, language, etc. come into play. Additional difficulties arise when attempting to predict human behavior. Sure, it's not hard to get a lot of info from raw data. But that doesn't mean it's not worthwhile to scale, restructure, impute, or otherwise engineer data for better predictions or to focus on certain specific data that answers the unique goals of the analysis. Much depends on what is being studied and how the alternative and null hypotheses are formed.

So good for the analyst, he found some raw data source(s) about covid that he could explore right off the bat, but depending on the questions asked, a good deal of additional work may, or may not be called for. It depends.
now that you say it... I have to admit I was only thinking of numerical data, not text. So stupid. Thx for bringing this to my (un)awareness!
 
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