A beginning Reflection on the Self-attestation of Scripture

How do we know the Christian God?  The question of existence, tied to the Scriptures


Introduction

This problem is from epistemology,  how do we know?
The application is religious, how do we know the Bible is inerrant and infallible?

Chapter 1: The pervasiveness of scripture's self-attestation of truth and authority

A common argument from conservative presbyterians is that the Bible is self-attesting, that is it says that it is infallible, reliable.  This argument falls on its face because of the "liar's paradox", where if the liar says that he is telling the truth, then he is actually lying. The only way out is to have some sort of evidence. 

However, the argument can be brought back to its feet again via the following steps:
1) Realize that the self-attesting method uses the idea of "proof-texting", where a verse is picked to prove something about other verses, in this case the whole Bible. So Jesus says in many places that the scriptures (the Old Testament) is of God, therefore reliable.
2) In the traditional approach, Jesus's reliability and that of the Bible are linked.  If you believe in Jesus, you must believe in the Bible.  This is an argument in the form of a dilemma.
3) Instead of the traditional approach, say that the teaching of the reliability of scriptures is "pervasive" throughout scripture (thanks to James Scott, in OPC denominational magazine, New Horizons, 2012).  By realizing that all the writers of scripture, including Jesus (as a source, since he technically didn't write) all operate from the paradigm that the scriptures are reliable, and as a group, they depend on God for inspiration (as in "tell me what to say, oh God" or "how should I react to the idolatry of Israel", ...), the dilemma is made larger.  Either accept the whole context of the people of God, who (some of whom) are the source of the scriptures, via the inspiration of God, or doubt one piece, in which case the doubter does not identify with the people of God. 

This method is a sort of reductio ad absurdum.  By making the problem much worse, we make it better (dialectic, i.e. dialogue).  Now instead of a few verses being used to make sweeping generalizations about the rest of scripture, we actually have a worldview that without a paradigm shift is either correct in toto or "deeply" wrong.

This is the situation for most people, today, I think, appreciating the Biblical writers and their view, but conflicted, feeling like they are outside looking in.

Chapter 2: A true believer: VanTil

See Why I Believe in God, by Cornelius Van Til.

In the first paragraph, Van Til explains both
1) he was raised as a Christian ("God is Himself the environment by which my early life was directed and my later life made intelligible to myself.")
2) argument for or against God is possible because of God's existence.

Thus Van Til is a "true believer" in the sense of enthusiasm, and not being conflicted.  See the quote "Arguing about God's existence, I hold, is like arguing about air.  You may affirm that air exists, and I that it does not. But as we debate the point, we are both breathing air all the time." 

Manufacturing models and cost estimation

When considering planning a manufacturing operation, obvious questions are:
1) how much will it cost per widget, including capital, labor, energy costs and so on!
2) Where will the costs be lowest, with transportation costs to markets included?
3) When should I build
4) How large should the operation be? How many manufacturing lines, and so on.

Of course, this is an issue from operations research, where one tries to optimize profits (producer model in microeconomics), with the realization that there are risks ...
1) of market size not being realized
2) market share not captured by my company

so that I end up with unused capacity.  Of course, the converse risk is not capturing market share because I have too little capacity!

For an engineering perspective, see

What Every Engineer Should Know about Manufac…

The equation for profit (please comment if I have this wrong ...!!!)  amortized over each item, given a manufacturing line that produces N widgets per year, sold at price p, in a plant that costs cap to build and is sold for cap $_f$ after depreciation with a factor depreciation factor each year, and has operating costs including labor, raw materials utilities, waste handling, etc., is

profit/N = $\gamma$ p - $\gamma^s $ cap * deprec factor - oper - p * $\Delta$ inventory

Note: The variable "s" is an exponent that reflects the scale of an operation.  So, expanding operations from N items per year (so $\gamma = 1$) to 2 N increases capital costs by $2^s$.  So, if s = 0.7, the doubling of manufacturing capacity increases capital costs by 62%.

So, just how big is the capital expenditure part for energy applications?  Daniel Yergin says "energy is a huge, capital-intensive business, and it takes a very long time for new technologies to scale" Yergin on energy scale.  For fossil fuel generators, for example, not only is the construction of a larger facility benefited by economics of scale, in operations, scale matters too, because there is a larger ratio of heat transfer surface inside the boiler than the surface of the enclosure, where energy is lost.

Bringing Domestic Manufacturing back; multiple dependencies

Reviving Domestic Manufacturing depends on  several factors
1) increased factory automation
2) cheap energy prices relative to competitor nations
3) supply chains and logistics advantages of keeping manufacturing close to the market

See John Mauldin's article (from GaveKal) which discusses factory automation, and what that could mean for the future of manufacturing in the US.  Domestic energy production is also supposed to be a big factor, because those automated manufacturing lines will be most competitive where the energy is cheapest.  Supply chains and logistics considerations will put the US in a competitive place once automation is in place, assuming energy prices can stay low.

Weeks when decades happen

For a gloomy view of the current manufacturing situation, with four ideas to turn it around, see
http://www.itif.org/publications/worse-great-depression-what-experts-are-missing-about-american-manufacturing-decline
from the Information Technology & Innovation Foundation 

The best technology does not always win

It is well known that A123 Systems is struggling, at least as evidenced by its stock price.  However, the factor(s) behind its difficulties are not so well known, and one could speculate about its technology, its financials, and the economics of its products.  A hint to the answer is discovered from one of a fanatical base of battery users that appreciate the technical advantages of A123 batteries.  They have superior cycle life (2000 cycles with 20% diminution of capacity), but have been replaced in DeWalt battery packs with inferior batteries. See the video for a demonstration of the superiority of A123 technology.

By process of elimination, it must be something about the economics of its products or the financials.  From the video, it is implied that its products are expensive, and that consumers may not be willing to pay more for this quality and safety.  Is it because they don't know about it?

motivation for studying domestic manufacturing

The following quote from Sen. Jeff Bingaman is a motivation for studying manufacturing, because it explains the consequences of losing domestic manufacturing share

Although the U.S. is one of the greatest sources of innovation in the world today, "it's not clear we are going to reap the benefits of that innovation, or even retain the advantage we have in that innovation,"In the ever-changing and highly competitive environment of high technology, the research and development necessarily follows the manufacturing, and before long the next generation of technologies are being developed overseas as well as the manufacturing occurring overseas. We've seen this scenario play out in such industries as televisions and consumer electronics and, in my view, it would be tragic if it happened again in the technology areas important to our energy future."

Sen. Jeff Bingaman, D-N.M, testimony March 13, Senate Energy and Natural Resources Committee

quoted from article in SNL, Independent DOE loan reviewer backs Chu's subordination of Solyndra loan, http://www.snl.com/

Manufacturing planning appears to be a bit of a black art.  The art is called "

Manufacturing resource planning" (see wikipedia http://en.wikipedia.org/wiki/Manufacturing_resource_planning), and all business processes are considered.  Unfortunately, in the picture on the wikipedia page (http://en.wikipedia.org/wiki/File:MRP2.jpg), budgets and projected sales are indicated in the flow, but these are just the values we need to project.  So, for instance, the budget for a manufacturing project starts with fixed costs such as building construction or rent, and then labor and raw materials must be considered.  All these will vary with projected sales over short run of the construction phase, and of course, the real sales over the long run.  More can be learned about this topic from producer theory in microeconomics, or from operations research, which is more mathematical and computer based.  Of course, the operations research/computational modeling approach deals with optimization of profit in a mathematical space consisting of capital investment, projected sales, etc.

The German translation of the wikipedia "integer linear optimization" planning lists production planning as an application of this theory.  An edited version of the  wikipedia at http://de.wikipedia.org/wiki/Ganzzahlige_lineare_Optimierung is quoted with editing, below:

Production Planning 

Production planning often involves the problem of determining production quantities for multiple products that share common resources (machines, labor, storage capacity, ...). For example, the optimization target is to maximize total contribution margin, without exceeding the available resources. In some cases this can be expressed using a linear program.

The entry goes on to say that "often the variables must be integers, for practical reasons."

Producer theory and deciding just how big to make a manufacturing operation

In today's global, fast-paced environment, it seems that capital intensive projects are hard to "get off the ground."  This goes for nuclear power plants, oil and gas pipelines and so on.  Another area of application is manufacturing.  As appears to be true in many markets, any initiative appears to take one into a sandbox with many other players.  Perhaps global competition for sales, talent, and ideas makes a person wary of risking too much.  If there is a new widget to produce,  how much should one risk to produce it?  How much capital should a company spend getting started?  How does one get investors interested?

This is the provenance of producer theory, a topic in microeconomics with analogies to consumer theory.  For consumers, utility is king, that is, how much happiness can I get for X dollars?  For producers, the question is how much profit can I make from fixed and non-fixed assets?  A professor Nolan Miller from Harvard has written some notes at http://www.hks.harvard.edu/nhm/notes2006/notes5.pdf that remind us of:
1) sunk costs -- once you construct a manufacturing plant for producing widgets Y, at most you can recover a small portion of the capital if production of Y never happens due to a lack of market size or market share.  Remanufacturing or flexible manufacturing may allow you to make Z, but remember there is ... (see next point)
2) no free lunch -- everything you do in pursuit of a buck is going to cost something, or at least risk something of value.  Otherwise, you could just ramp up the operation to huge levels and be wealthy beyond measure!
3) possibility of inaction -- although this seems very uncool to Americans, there is something to be said for doing nothing rather than doing the wrong thing and losing your shirt!
4) Free disposal -- this part is probably just for mathematical purposes, but a lesson here is don't make something just because you have employees sitting around doing nothing or some extra raw material lying around.

Some notes from "in the news", below

A quote from Wired makes it clear just how expensive the investments in manufacturing capability and capacity can be ...
Solyndra’s $535 million loan guarantee closed in September 2009. The firm had no problem putting the funds to use, starting construction on a second factory, expanding its workforce to 1,100 employees, and paying millions for a custom machine designed to put the finishing touches on the cells at a rate of 60 per minute. As part of an ongoing “Main Street tour” highlighting the nation’s manufacturing prowess, Obama scheduled an appearance at the Solyndra factory in May 2010. After a tour of the facilities, the president gave a speech on the factory floor in which he called Solyndra “an engine of economic growth.” “The future is here,” he added.
source: http://www.wired.com/magazine/2012/01/ff_solyndra/all/1

The Wired box about manufacturing start-up costs puts some numbers up that can be used in a back of the envelope type analysis:

Ramp-Up Costs

Gearing up to manufacture a new consumer product is notoriously expensive. In the energy sector, the costs can be crushing, as Solyndra found out: It spent at least $87 million to outfit its first factory and get to market, $290 million in research and development, and $733 million on just the first phase of its second factory, which was necessary to manufacture at the required scale. 

source: http://www.wired.com/magazine/2012/01/ff_solyndra/all/1

Microeconomic theory of manufacturing in a technologically advanced economy

The issue of reviving domestic manufacturing in the United States is very much in the news.  An important subset of this question is whether government and utility initiatives such as Smart Grid can reverse the decades long decline in US manufacturing output [verify with graph].  An important place to start is the microeconomic theory of producers and consumers, which hopefully gives insight into the problem of how much capital to risk in a manufacturing venture.  The relevant variables should be market size, market share, raw materials costs, equipment costs, tool and die costs, and labor costs.  A good reference is available through MIT OCW free of charge at http://ocw.mit.edu/courses/economics/14-01sc-principles-of-microeconomics-fall-2011/unit-3-producer-theory/introduction-to-producer-theory/.   This reference introduces the marginal decision rule, a tool for calculating/determining the maximumally profitable strategy.  In the example in chapter 8 of the course textbook, an example of street sweeping is used--the Chinese use an army of human street sweepers, whereas in the US, machines sweep the street.  In the US, higher labor costs drive decisions to mechanize and automate.  This relates to the motive for increased automation that drives the Smart Grid market, and indirectly drives increases in demand for manufactured products.   The relevant variable is market size.

However, the question I want to ask is, how much capital does one risk to start a manufacturing enterprise?  How many widgets do you plan to make per day, based on anticipated market size, market share (due to competition), and various input costs, including labor.  In the case of smart meters, if the rate of adoption is high, the market will saturate sooner.  This means that any manufacturing operation of sufficient scale to meet high artificial demand (due to government driving market) may be idle within 5 years, as opposed to 20 years, if  smart meters are replaced gradually.

The dilemma for government regulators and policy analysts is how to encourage economic growth through rapid adoption of technology without bankrupting high capital supporting operations such as manufacturing concerns. [this is actually the thesis for a post in its own right]