‘The People With Something To Hide”

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8 Responses to ‘The People With Something To Hide”

  1. G W Smith says:

    Thanks Tony! It’s incredible how they will lie blatantly, over and over, yet the dems always looks the other way. Obviously, the collectivist narrative is more important than the truth. Hitler, Stalin, Mao, et al, thought the same way.

  2. Jeff L. says:

    Great video Tony! You should have added this tidbit about Obama spending millions to hide his college records. (Presumably, he hid them because he was receiving foreign student scholarships.)

    https://www.cbsnews.com/news/obama-administration-spent-36m-on-records-lawsuits-last-year/

  3. Brian D says:

    Shouldn’t the oceans be darn near boiling by now, or NOT!
    https://weather.gc.ca/data/saisons/images/2021060500_054_G6_global_I_SEASON_tm@lg@sd_000.png

    If that link goes bad, go here. Click “Daily” (Note: links gone late evening Canada time. they’re back up a.m. their time.)
    https://weather.gc.ca/saisons/sea-snow_e.html

  4. Conrad Ziefle says:

    It seems that taking a position on global climate change is easy: Either you accept the data taken by actual scientific instruments, or you believe the output of video game simulation models.

  5. Thank you Tony. Your clear observations of what the facts actually are and what “climate experts” said then and now are required reading. Please keep it up!

  6. Richard says:

    the HIDE is about $$$$$$$$, they tell us its about the environment when its really about $$$$$$$

  7. Stephen J Bradford says:

    Are you not publishing on Rumble anymore, Tony?

  8. Winston says:

    I have a question about what I believe to be a FUNDAMENTAL and easily understood flaw in any attempts at climate projections which I have never seen explicitly covered.

    Very long term, thousands of years or longer, climate graphs containing temperature, CO2, etc., plots are very complex as if defined by a huge number of individual equations added together (which they are).

    The oldest climate computer model projection graphs I’ve seen date back only to 1975 and even over that short period of time don’t match observations. Even if they did, how could matching such an extremely short segment of climate variation EVER be assumed to represent an accurate model of climate?

    Only if a model which matched current climate changes was used to project far backwards in time and actually matched past variations could any accuracy claim be made for that model and if the past is too inaccurately known to do that test then matching such a short period in current climate variations proves absolutely nothing about the actual accuracy of the model.

    An article I found many years ago:

    Verification, Validation, and Confirmation of
    Numerical Models in the Earth Sciences
    Naomi Oreskes; Kristin Shrader-Frechette; Kenneth Belitz
    Science, New Series, Vol. 263, No. 5147. (Feb. 4, 1994), pp. 641-646

    https://pdfs.semanticscholar.org/c6e1/385abc386c3519175e34ea3c0a68da8b540c.pdf

    Excerpts:

    Verification and validation of numerical models of natural systems is impossible. This is because natural systems are never closed and because model results are always non-unique. Models can be confirmed by the demonstration of agreement between observation and prediction, but confirmation is inherently partial. Complete confirmation is logically precluded by the fallacy of affirming the consequent and by incomplete access to natural phenomena. Models can only be evaluated in relative terms, and their predictive value is always open to question. The primary value of models is heuristic.

    Numerical models are increasingly being used in the public arena, in some cases to justify highly controversial decisions. Therefore, the implication of truth is a serious matter. The terms verification and validation are now being used by scientists in ways that are contradictory and misleading. In the earth sciences-hydrology, geochemistry, meteorology, and oceanography-numerical models always represent complex open systems in which the operative processes are incompletely understood and the required empirical input data are incompletely known. Such models can never be verified.

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