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The Forum > Article Comments > A democratic approach to population and development > Comments

A democratic approach to population and development : Comments

By Philip Howell, published 5/8/2013

Adding a question to the census could allow us to control housing density from the bottom up.

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Hi Fester,

Great points and you have identified a fatal flaw in the CAGW debate.

Firstly the complex analysis used in such as entity relationship analysis, process engineering and enterprise mapping have one outstanding difference, they do NOT involve computer modeling, computers are not even required to produce results other than producing the report and graphs. The variables must be actual (empirical), not simulations.

These tools mandate examining what is real, tangible, measurable and quantifiable which is why these tools are so powerful. We also know that they work because most large enterprises on the planet are horrendously complex and have to work in the real world by using such tools.

I hope you can now see that CAGW as a topic involves only one of the six domains, science, and that science relies on assumptions, simulations and forecasts. Nothing is real in that sense because it is viewed in isolation.

CAGW relies on just part of just one of the “thumb wheels” of the combination lock analogy. More importantly, if CAGW were subjected to the methods we are discussing here it would be seen for what it really is, a compete fabrication.

Likewise when subjected to this methodology, the “Peak Everything” mantra will fail, it will fail because they assume that the “something” being peaked is the primary influence and ignores thousands of other factors embedded in several other domains.

Remember, no simulations, no modeling, no isolated assumptions and no such thing as independent variables, they all have a relationship and an impact.

Try the pyramid analogy, at the tip of each domain there are few entities but the further you go towards the base of the pyramid, the more the entities and the more complexities. The principle is to take one entity at a time and trace it down into the mass of complexities but only register that which has a “relationship” with the entity, ignoring the rest. Does that work for you?

Thanks for your questions and interest.
Posted by spindoc, Friday, 9 August 2013 8:31:38 AM
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Thank you, S.

So your approach is one of optimising the system for the current conditions. That seems most sensible, and probably leaves you in the best shape to meet problems as they arise. But is there still a role for prediction? My experience of forecast accuracy leaves me with little confidence in them, especially anything long term. Freeman Dyson sees long term forecasting as far too complex to have any reliability, and so advocates not acting on them.

ongnow.org/seminars/02005/oct/05/the-difficulty-of-looking-far-ahead/

On the growth question, I also look at observations of countries where family planning programs have been implemented, and guess it is the success of these programs that leaves me sceptical of the benefit of growing the population faster than other developed nations.
Posted by Fester, Saturday, 10 August 2013 7:39:55 AM
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Fester, it’s nice down here in the dungeon of a thread that has dropped off the radar, seems we get a quiet chance to think about things.

You ask, << Is there a role for prediction? >> No. Prediction relies on forecasting, which in turn relies on assumptions which then have to be modeled. Each any every time you change an assumption you change the outcome. Worse still, the people who write the algorithms are called “Quant’s”, sadly today the “Quant’s” are often part of the value part of assessment and that should never be allowed. (The Freeman Dyson effect)

The processes I describe rely on trend lines; this is what has actually happened and not what might happen. So of all the variables (potentially millions), the first task is to identify what in each of the six domains could have an impact and then which entity within each domain has a relationship to an outcome you wish to test. Then ask the question, which if any entities are actually changing?

What you then have is a much shorter list of “tested” entities to work with, this why such systems are vastly more accurate than modeling. Modeling is much more popular with those who wish to “drive” an outcome rather than to actually “discover” one.

I think you asked me earlier for an example. Not easy without actually going through the process on a live example. I’ll try with your “population” example.

Firstly each country will obviously be vastly different, so until you have ALL countries mapped, you cannot start on global. Within each country, each region will be different so you have to drop down to the lowest level of granularity to start.

Then you start interrogation of all the historical factors impacting population sustainability in that region. You do this for every region in every country and consolidate upwards.

Then you look at any additional factors that might apply in different countries that do not apply in others. You also need to look at issues that originate outside the country but might apply somewhere else. (Cross relationships)

Cont’d
Posted by spindoc, Saturday, 10 August 2013 11:57:18 AM
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Cont’d

So for a particular region you might look at the impacts of religion, economics, public policy(e.g. family planning), health, agriculture and culture for example. (All drawn from the SPERES domains)

Every entity must be mapped as relevant to “population sustainability” and tested for a relationship then quantified against the prevailing trend line. So the process cascades down into “relevant only” content and is consolidated upwards to produce a global picture.

You can now see that each domain (X 6) contains thousands of entities but not all are relevant to topic. Once you’ve tested a detailed understanding of all the issues that impact by region, by country and internationally and have the trend lines for each, decisions can be taken on the historical reality and not predictions. Rather these tools rely on a closed loop corrective cycle to constantly respond to any significant changes in the monitored trend lines.

As always, you can make all the decisions you like however, you will still have the problem of applying these. Unless every nation agrees to what is proposed as the “solution”, have the resources to implement them and the political will to deliver against any negative impacts, there is no point.

Consider peak population, oil, food production and resources. Each is a different aspect of the same sustainability paradigm and yes, solutions based on reality can be found but sadly, not implemented.

The closest we have ever come to a solution is a global response to CAGW. There was once a global agreement, trading markets to fund it and renewables industry to implement it. These are now gone because the science upon which these were based is flawed.

That said, had these processes been applied in the first place there would not have even been any CAGW or Peak something alarmism in the first place.

Hope this works, have a great weekend.
Posted by spindoc, Saturday, 10 August 2013 11:58:08 AM
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Yes I did thanks, S. Thanks for a very detailed reply. I guess that living in the present is complex enough, and as it is all we live in we should make the most of it.
Posted by Fester, Monday, 12 August 2013 5:33:06 PM
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