Principles of science and ethical guidelines for scientific conduct (v8.0)

Introduction
1 The principles of science
2 The ethical guidelines for scientific conduct
3 Definitions
4 Arguments for the principles of science
5 Arguments for the ethical guidelines for scientific conduct
6 About the perspective on definitions and truth
(about 6400 words in total)

Introduction

Every day, numerous statements about how things relate to each other can be seen and heard everywhere. Science is normally thought of as the way of conduct that provides certainty about such relationships. However, beliefs and unsubstantiated statements can often be seen, also within science.

So, what are the principles of science then?
It is hard to say, as a well-defined set of principles for science does not seem to be readily available.

That position is supported by the following quote from National Academy of Sciences:
“The basic and particular principles that guide scientific research practices exist primarily in an unwritten code of ethics. Although some have proposed that these principles should be written down and formalised, the principles and traditions of science are, for the most part, conveyed to successive generations of scientists through example, discussion, and informal education.”
Ref.: Responsible Science, Volume I: Ensuring the Integrity of the Research Process; Panel on Scientific Responsibility and the Conduct of Research

What can be found in abundance, however, are codes of conduct like Singapore Statement on Research Integrity,  EPA’s Principles of Scientific Integrity, Max Planck Society – Rules of good scientific practice or  The European Code of Conduct for Research Integrity. But none of these provides a well-defined set of basic principles.

Even an highly influential work within the philosophy of science: “The logic of scientific discovery”, by Karl Popper, does not provide a set of well-defined principles. See section “5 Perspective on definitions and truth” in this work for an elaboration.

The many controversies about scientific issues indicate that it would be beneficial to have the basic principles of science defined. Unfortunately, it is not obvious what these principles should be.

This work is based on the assumption that a set of principles can be defined – and is nothing less than a bold attempt to provide a set of fundamental principles that can be used to distinguish independent verifiable knowledge from beliefs – or to recognise “fake news” or “dubious science” for that matter.

The principles provided here have not been taken out of thin air. Some principles may be recognised as principles phrased in various ways in various sources. Others are distilled from existing international standards. However, this is an original work that provides a unique set of well-defined principles for science.

This work itself, or parts thereof, can be proven wrong simply by identifying a flaw, a logically invalid principle or a flawed definition. It can also be proven wrong by identifying a concept known to be true that can not be put forward in a way that complies with all relevant principles or a concept known to be wrong that complies with all relevant principles. 

The idea that a set of well-defined principles for science does not already exist may also be wrong since it is hard to prove that something does not exist. Anyhow, that idea can also be proven wrong simply by providing a link to such principles.

All significant words that are used in this thesis are defined in section 3. The reason why most terms are defined within this work is that there are many different dictionaries available at the fingertips of any reader. This work cannot rely on undefined terms or terms having various definitions, as even slightly different definitions will change the conclusions that can be drawn on the basis of this work and possibly make it inconsistent or logically invalid.

This work may be reproduced on the condition that the reproduction includes a link to the original site: https://principlesofscience.wordpress.com

1 The principles of science

The principles of science:

§P1 The clarity principle

A scientific argument consists of clearly stated premises, inferences and conclusions.

§P2 The traceability principle

A scientific premise is verifiable. Premises and their sources are identified and readily available for independent verification.

§P3 The logical validity principle

A scientific inference is logically valid.

§P4 The deduction principle

A scientific conclusion is deduced by application of axioms, definitions, and theorems, measured properties and scientific concepts that have already been verified or validated.

§P5 The logical construction principle

A scientific concept consists of statements that are logically valid conclusions deduced from premises that are themselves logically valid conclusions, axioms, definitions or theorems.

§P6 The definition principle

A scientific concept is well-defined and has a well-defined capability of prediction within a well-defined context.

§P7 The validation principle

A scientific concept can only be validated by comparison of predictions deduced from that concept with measurement results. Whenever predictions differ from measurement results, by more than the combined uncertainty of the measurement results and the claimed capability of the concept,  there must be something wrong with the concept – or the test of it.

§P8 The context principle

A scientific concept can only be referred to as validated for the context covered by the validating tests.

§P9 The data availability principle

A scientific statement is based on verifiable data. Data and precise information about how that data was obtained are readily available for independent verification. Whenever data are corrected or disregarded, both uncorrected and corrected data are provided together with a scientific argument for the correction.

§P10 The measurement report principle

A scientific measurement report contains traceable values, units and stated uncertainty for well-defined measurands in a well-defined context.

§P11 The prediction report principle

A scientific prediction report contains values, units and claimed capability for well-defined measurands in a well-defined context.

These principles can only be interpreted as intended by applying the definitions in this thesis. To keep traceability to a full account with definitions and explanation, these principles can only be reproduced on the condition that a link to this version of the thesis is included.

2 Ethical guidelines for scientific conduct

Having defined the principles of science, the principles for true and independently verifiable knowledge, it is now possible to define basic ethical guidelines for scientific conduct. Each ethical guideline on this list is derived from and corresponds to the principle of science in section 1, having the same numer.

Ethical guidelines for scientific conduct

§E1 The clarity guideline

State clearly the premises, inferences, and conclusions of an argument.

§E2 The traceability guideline

Verify that premises comply with the principles of science, identify premises and their sources and make sure that these are readily available for independent verification.

Cite precisely the referred source and identify all information used as a premise.

§E3 The logical validity guideline

Use logically valid inferences.

Whenever the truth of the premises does not guarantee the truth of the conclusion, identify clearly the argument as a feeling, judgement, belief, opinion or hypothesis.

§E4 The deduction guideline

Put forward conclusions in such a manner that an independent party can verify that a conclusion  is correctly deduced from axioms, definitions, theorems, measured properties, and validated scientific concepts.

§E5 The logical construction guideline

Put forward concepts in such a manner that an independent party can verify that the concept is correctly constructed by logically valid conclusions, axioms, definitions or theorems.

§E6 The definition guideline

Define a concept, its capability, and applicable context in such a manner that the concept can be independently tested.

§E7 The validation guideline

Validate concepts by comparison of predictions from that concept with observations. Only refer to concepts as validated  when predictions repeatedly match observations within combined uncertainty of the measurements and the claimed capability of the concept and no sound counterargument can be found.

Ensure that those who are influenced, curbed, or entitled to the propounded concept or product are also entitled to have the product independently tested.

§E8 The context guideline

Only refer to a concept as validated for the context covered by the validating tests.

§E9 The data availability guideline

Base statements on verifiable data and make sure that data and precise information about how that data was obtained are readily available for independent verification. Whenever data are corrected or disregarded, provide both uncorrected and corrected data together with a scientific argument for the correction.

§E10 The measurement report guideline

Ensure that measurement reports contain traceable values, units, and stated uncertainty for well-defined measurands in a well-defined context.

§E11 The prediction report principle

Ensure that prediction reports contain values, units and claimed capability for well-defined measurands in well-defined contexts.

These guidelines can only be interpreted as intended by regarding the principles and by applying the definitions in this thesis. To keep traceability to a full account with definitions and explanation, these principles can only be reproduced on the condition that a link to this version of the thesis is included.

 

3 Definitions

abstraction: the creation of a concept representing a relationship between or among entities
accept: regard to be true
accidental: not intended
argument: a conclusion inferred from a set of premises 
assault: harmful action towards
attribute: a characteristic used to describe or define a thing
axiom: a statement that is self-evidently true and accepted as a true starting point for further deduction
basic: an essential premise that is part of the foundation of a logical system
behavior: a set of actions
belief: an acceptance that something is true without proof
calibration: comparison of a measurement with a reference having a known uncertainty
capability: ability to do something
capability (of a concept): ability to predict an outcome within a maximum difference between predictions and measurements
clearly stated: stated in a manner that it is only open to the intended interpretation
comparison: quantification of the difference between
comprehension: the ability to understand something
concept: any expression of a relationship between two or more measurands
conclusion: a statement inferred from one or more premises
conduct: the manner in which a person behaves
consideration: careful thought
consistent: not causing any contradictions
context: a set of those things that have an influence on an observed, measured or predicted value
contract: an explicit or implicit agreement by which a product is judged to be right or wrong
contradict: demonstrate that a statement is not true
correct (about data): replace a measured or predicted value with another value
culture: a way of perception, reasoning, or behavior that is largely accepted by a group and promoted as the correct way to perceive, think about, or act.
data: measured or predicted value of a measurand or relationship between measurands
deception: a false representation of something
deduction: a combination of premises into a conclusion by means of mathematics and logically valid inferences
definition: a set of distinguishing characteristics
deprive: prevent a person from having or using
detrimental: tending to cause harm
disregard (about data): remove a value from a series of data that is used as a premise
document: an identified collection of words, numbers and symbols
ethical: evaluates to being right when evaluated by the means of a moral standard
ethics: a set of principles that evaluates to right when evaluated by a well-defined moral standard
false: a statement that can be contradicted by a sound argument within the defined context
falsehood: something that is not true
falsified: contradicted by a sound argument within the defined context
fool: cause someone to accept as true something that is false by committing fraud
founded: being dependent on
fraud: promotion of a concept that is not true
guideline: a recommendation that complies with a set of principles
harm: cause damage
harmful: can possibly harm
hypothesis: a propounded statement or concept that has not been verified or validated
identity: a set of distinguishing characteristics
inconclusive: can not currently be evaluated to true or false
independent: not under influence of the party propounding a concept
infected: being negatively influenced by
inference: logical connection between premises and conclusion
interpreted: made clear
judge: evaluate
judgement: considered evaluation
lie: a falsity put forward as true
logically valid: the truth of the premises guarantees the truth of the conclusion – it is impossible for the premises to be true and the conclusion nevertheless to be false.
mathematics: a consistent and logically valid system of symbols and operations on these symbols
measurand: well-defined property that can be observed or quantified by a measurement
measure: quantify a measurand by establishing the ratio between that measurand and a reference that serves as a unit – and assign a number representing that ratio, and the associated unit, to that measurand
measurement (result): a measurand quantified by a value and an associated unit
mental: of or pertaining to the mind
metaphysical: of or pertaining to the conceptual model of reality an individual has developed
mind: the element of a person that enables him to be aware of the world, perform abstractions, form concepts, think, feel, and act
moral standard: an objective standard by which actions are evaluated to be right or wrong
morally sound: evaluates to right, when evaluated against a moral standard
mysticism: a system of beliefs that can not possibly be verified by an independent person
nature: any thing and any relation between things
objective: well-defined, and available for independent consideration where a sound consideration will lead to the same conclusion
observe: conclude if an attribute is in accordance with a definition
precise information: sufficient for replication by an independent person using equal tools
prediction: quantification of a measurand without any foreknowledge about an eventual measurement result
premise: a statement used to infer a conclusion
principle: a proposition that serves as a premise in a system of reasoning
promote: actively put forward as true
property: an attribute that can be observed or measured
proposition: a set of words or symbols having an intended interpretation
propound: put forward for consideration
prove: demonstrate the truth of a statement by means of axioms, definitions, theorems, or tests
publish: make available to the public
readily available: available without further request
reason: a persons use of his mind to evaluate the truth of proposition or set of propositions by means of words, symbols and logic
reference: a measurement device or procedure that has an unbroken chain of calibrations to the definition of the unit
relationship: a quantified change in measurand A is followed by a quantified change in measurand B
research: systematic investigation in order to establish facts and draw conclusions
science (noun): an enterprise engaged with the development of true and independently verifiable concepts
scientific: consistent with the moral of science
scientist: a researcher that publish findings in accordance with the moral of science
self-possession: that a person enjoys, over himself and his powers, full and exclusive rights of control and use, and therefore owes no service or product to anyone else that he has not contracted to supply
sound: a conclusion that is logically valid and based on true premises
source: identified document containing a premise
statement: a logical proposition that can be either true or false within the defined context
test: an activity that can verify or validate
theorem: a conclusion that has been proven and that can now be used as the basis of other proofs.
thing: whatever that can be defined
traceable (about measurements): having an unbroken chain of calibrations to the definition of the unit
true: a statement that can not be contradicted by a sound argument within the defined context
uncertainty: quantified accuracy
unethical: evaluates to false when evaluated by the means of a moral standard
unit: a well-defined quantity that has one unique value
validate: demonstrate the truth of a concept within a well-defined and applicable context
verify: demonstrate the truth of
well-defined: defined in such a manner that it is only open to the intended interpretation by independent and sound consideration
will: the faculty by which a person decides on and initiates action
wrong: not true

4 Arguments for the principles of science

Introduction

It should be noted that one of the ideas with this work has been to provide fundamental principles of science and corresponding ethical guidelines in a compact manner. A significant effort has been invested in limiting the amount of text to an essential minimum.

Regarding §P1:
A scientific argument consists of clearly stated premises, inferences, and conclusions.

The constituents of an argument can be recognised in §1 and the associated definitions.

Within science, it should be possible to verify that an argument is sound – that the argument is based on true premises, and that the truth of the premises guarantees the truth of the conclusion. 

An essential characteristic of science is that arguments should be independently verifiable. To be able to verify that an argument is sound, the intended interpretation must be clear.  An argument that is open to multiple interpretations can not be verified by an independent party as it can not be known which interpretation is the correct one to verify.

Regarding §P2:
A scientific premise is verifiable. Premises and their sources are identified and readily available for independent verification.

A premise can only be verified if it is properly referred to. Both the premise itself and the source containing the premise should be identified, and the source should be available for verification.

If a premise can not be verified, the premise can only be accepted on the basis of a belief in the proponent of the argument.

Regarding §P3:
A scientific inference is logically valid.

If an inference is not logically valid, it follows from the definitions that the truth of the premises does not guarantee the truth of the conclusion – it is possible for the premises to be true and the conclusion nevertheless to be false. Hence, the conclusion can then only be accepted on the basis of some kind of belief.

Regarding §P4:
A scientific conclusion is deduced by application of axioms, definitions, theorems or measured properties and scientific concepts that have already been verified or validated.

A scientific conclusion may be applied in an argument for or against a propounded statement or concept, or as part of a scientific concept.

A logically valid construction that ends up in a conclusion has to be based on something. In the case of abstract constructions like mathematics, the basis for the construction will be axioms, definitions, and theorems.

In the case of constructions intended to provide a correspondence between an abstract construction and observations and measurements of nature (like physics), the axioms, definitions, and theorems may be about nature or about the correspondence between an abstract construction and nature. In this case, the construction may also be based on observed or measured properties or scientific concepts that have already been verified or validated.

As an example, it will normally be acceptable to base a scientific conclusion on a concept like Newton´s laws of motion within their validated context, or on a measured property like the gravitational acceleration (approximately 9,8 m/s^2 on earth). The application will dictate how accurate that measured property will have to be – whether 9,8 m/s^2 is sufficiently accurate or if a more accurate value is required.

Regarding §P5:
A scientific concept consists of statements that are logically valid conclusions deduced from premises that are themselves logically valid conclusions, axioms, definitions or theorems.

The entire concept will have to be a logically valid construction that has a well-defined and true basis. If there are any logical fallacies in a construction, the result will be that the concept can only be accepted on the basis of some kind of belief.

A concept that is under construction, or has not yet been validated, should be clearly identified as an hypothesis to avoid premature application of the concept.

Regarding §P6:
A scientific concept is well-defined and has a well-defined capability of prediction within a well-defined context.

To facilitate independent judgment, the concept itself will have to be well-defined. If the concept is not well-defined, it can not be tested by an independent party. An independent party will not know what to test and how to test it. 

Concepts are only valid within a context. One example of this is classical physics: “Beginning at the atomic level and lower, the laws of classical physics break down and generally do not provide a correct description of nature.” (Ref.: Wikipedia; classical physics; at the date of publishing this work). To facilitate judgment of a concept, the context for which the concept is claimed to work well will have to be defined.

Many concepts got a capability of prediction of the value of a measurand, but not exactly. A concept may have a capability of prediction with some uncertainty. To facilitate judgment of a concept, the capability of the concept will have to be defined. If not, there is no way to tell if the concept performs as claimed or not, or whether it is useful for an intended use or not.

Regarding §P7:
A scientific concept can only be validated by comparison of predictions deduced from that concept with measurement results. Whenever predictions differ from measurement results, by more than the combined uncertainty of the measurement results and the claimed capability of the concept,  there must be something wrong with the concept – or the test of it.

Any collection of words, numbers, and symbols is an abstract construction that may or may not correspond with observations and measurements of nature.

Within many areas of human expressions, like in politics, religion, love, hate, humor or whatever; it may not matter if an expression corresponds with nature. An essential characteristic of a useful scientific concept, on the other hand, is that of correspondence between predictions of that concept and observations and measurements.

Even if a concept complies with §1 to §6, there is no guarantee that the concept is a complete construction that also provides a correspondence between that concept and observations and measurements of nature. Without testing it, it can not be known for sure that the concept is complete, that there are no errors in it, that the concept is correctly constructed or that the concept actually has the claimed capability of prediction.

The only way to know that a concept performs within the claimed capability, within a defined context, is to deduce predictions from that concept, measure nature within the same context and see if the difference between predictions and measurements is within the claimed capability of the concept.

In judging the results of the test, the uncertainty of the measurements will have to be taken into account. Repeated tests are required to ensure that the results are representative.

There are many ways to adjust a concept to match observations and measurements. Many kinds of curve fit, parameterisation, change of definitions or addition of hypotheses can be used to adjust a concept. The problem with adjustments, however, is that adjustments may hide that the concept does not have the claimed capability of prediction.

Some concepts may need some kind of basic calibration and adjustment, but if a concept really has the claimed capability to predict the value of a measurand, there should be no reason to adjust the concept to a particular test.

The reason why it is so useful to compare predictions with measurements is that all kinds of adjustments of the concept to match measurements are logically impossible. It is impossible to adjust a concept to match something that is not yet known. Prediction excludes all kinds of adjustments of the concept to match the measured values.

There may be other ways to validate a concept, but all other ways leave a possibility that the concept has been adjusted to match measurements. Hence all other ways to validate a concept should also be followed by a scientific argument proving that the concept has not been adjusted to match the measurements of that particular test.  Without such proof, the concept can only be accepted on the basis of a belief that the concept has not been adjusted particularly for that test.

If a concept is not tested by an independent party, the concept can only be accepted on basis of a belief in the party propounding a concept.

Regarding §P8:
A scientific concept can only be referred to as validated for the context covered by the validating tests.

A test is performed within a context. Obviously, the test is only valid for that context.  As a principle, the concept can only be referred to as validated for the context covered by the validating test.

It may be that interpolation or extrapolation to some extent can not be contradicted by a sound argument, but that is not normally the situation.

However, the party propounding a concept might be able to put forward a scientific argument for the validity of interpolation or extrapolation, and it might be that no opponents are able to put forward a counter argument. Anyhow, extrapolation or interpolation should be followed by a scientific argument.

Regarding §P9:
A scientific statement is based on verifiable data. Data and precise information about how that data was obtained are readily available for independent verification. Whenever data are corrected or disregarded, both uncorrected and corrected data are provided together with a scientific argument for the correction.

Whenever a statement is based on observations or measured or predicted values, the data should be readily available for independent verification. If not, the statement can only be accepted on the basis of a belief.

There might be errors in the experiment that produced the data. Such errors can possibly be revealed by an investigation into how the data was obtained or by an independent replication of the experiment.

Anyhow, the statement can only be verified if precise information about how that data was obtained is readily available. If not, the statement can only be accepted on the basis of a belief.

Finally, it can be irresistible to disregard or correct data. There may be scientific arguments for doing that. If so, those arguments should be verifiable. If not, data should not be corrected, discarded or disregarded.

Regarding §P10:
A scientific measurement report contains traceable values, units and stated uncertainty for well-defined measurands in a well-defined context.

Obviously, a measurand will have to be well-defined, how else can anybody know exactly what has been measured?

Also, the measurement result will also have to be provided as a value together with the associated unit. A value without a unit is meaningless.

By using a unit in accordance with the International System of Units, the unit will already be well-defined. If the unit is a non-standard unit or even a hitherto unknown unit, the unit will have to be properly defined in the measurement report.

Whenever a measurement is performed by some kind of measurement device, the measurement device should be traceable by an unbroken chain of calibrations to the definition of the unit. Without a traceable measurement device, there is no way to know if the measurement is accurate, there is no way to quantify the uncertainty of the measurement.

Regarding the uncertainty of a measurement, the introduction to the following free and readily available guideline: Guide to the expression of uncertainty in measurement;  JCGM 100:2008, explains why quantification of uncertainty is essential:  “When reporting the result of a measurement of a physical quantity, it is obligatory that some quantitative indication of the quality of the result be given so that those who use it can assess its reliability. Without such an indication, measurement results cannot be compared, either among themselves or with reference values given in a specification or standard.”

For the principles provided in this work, it is regarded sufficient to state that it is essential that the uncertainty of a measurement is provided in the measurement report. Obviously, there are benefits in providing the uncertainty in accordance with an international standard or guideline. By not providing the uncertainty in accordance with a standard or guideline, there is a risk that the measurement report is regarded insufficient and that no judgments can be made on basis of that report.

Finally, it is also essential that the context for the measurement is well-defined. All the things that are known to have an influence on the value of the measurand should be identified.

(This principle has been based on section 7.2.1 in the freely available international guideline: JCGM 100:2008; GUM 1995 with minor corrections; Evaluation of measurement data — Guide to the expression of uncertainty in measurement.)

Regarding §P11:
A scientific prediction report contains values, units and claimed capability for well-defined measurands in a well-defined context.

This principle is an analogue to §10 about measurement reports, this should be no surprise since predictions are supposed to be comparable with measurements. A claimed capability may be expressed and documented in the same way as the uncertainty of a measurement.

5 Arguments for the ethical guidelines for scientific conduct

The moral of science

Ethics are based on an objective moral standard by which right and wrong are evaluated. The perspective on scientific conduct taken in this work is that:

The standard of value for science, is the abstraction of concepts that are true and independently verifiable.

That perspective is here regarded to be morally sound because it is consistent with the nature of ´the wise man´ – Homo sapiens, which possesses a unique capability to make abstract concepts from observations. His concepts compose his metaphysical world view that determines his reason, judgment, and behavior. Fundamentally, true concepts are essential to survival and prosperity of individuals and societies they form. Lies are detrimental.

Further, it is here realized that a person’s reason, judgment, and behavior define his identity. Belief in a falsehood tend to occlude comprehension of all that is contradicted by it. Once accepted, a falsehood may resist correction with great tenacity.

The perspective on scientific conduct is also based on the objective moral standard of self-possession: a person owns his body and mind. Hence, it is unethical to harm or deprive a man of his free will (except in self-defense). It is realized that a falsity may potentially make physical or mental harm to, or curb, others.

Even though each individual is responsible for what he believes or not, a deception published as science is fraud. Fraud is an assault on reason, man´s basic tool of survival, and consequently is unethical. Errors published in the name of science can be harmful to any mind infected by them. Furthermore, ideas can rapidly propagate globally, affecting millions.

Ethics of science

By the perspective of science taken in this thesis, it is unethical to promote falsehood. The basic ethical principle of conduct for the scientist, therefore, is:

First of all, do no harm – do not put forward unproven concepts as truth.

Therefore, any concept put forward as truth must be a logically valid structure where premises are true, and the truth of the premises guarantees the truth of the conclusions. A true concept can not contradict its own premises.

Logical basis

This thesis is founded on these three axioms:

The law of identity: a thing is itself. (For all A: A = A)

The law of non-contradiction: A thing can not simultaneously be and not be. In other words, two or more contradictory statements cannot both be true in the same context at the same time: ¬(A∧¬A)
(Symbols: ¬ = not ; ∧ = and )

The law of excluded middle: Truth is a binary alternative. In accordance with the law of excluded middle or excluded third, every logically valid proposition evaluates to true or false. anything that is not true is false: A∨¬A
(Symbol: ∨ = exclusive or )

About hypothesis

An hypothesis is here defined to be an inconclusive proposition. If one or more hypothesis are significant in the construction of a concept, the entire concept is inconclusive, i.e., hypothetical. A proposition that has neither been proven nor falsified is inconclusive. What is inconclusive is not a logically valid proposition.

There is nothing wrong in propounding an hypothesis within scientific conduct, as long as the hypothesis is clearly identified as an hypothesis. What is true of an hypothesis is that it is an unvalidated proposition and nothing more.

Unscientific concepts

Concepts that demonstrably can not possibly be evaluated to true or false contradict the standard of scientific value, as defined here, and belong in the category ‘mysticism’.

Applicability of ethical guidelines for concepts that are not of any interest to the public

By right, a scientist is free to do whatever he likes for himself and to himself. Ethical guidelines for science only becomes relevant the moment a scientific statement, argument, or concept is applied or published in the name of science in a way that directly or indirectly can cause harm to other humans.

Whatever a scientist do for himself, his employer, or his customer – is judged by a contract between himself and his employer or customer. However, error or fraud is detrimental by nature. Principles of science are useful to avoid deception of oneself or others.
«The first principle is that you must not fool yourself, and you are the easiest person to fool.»- Richard Feynman

The need for supplemental ethical guidelines

These guidelines are only concerned with actions that are directly related to the provision of true and independently verifiable statements and concepts, and not about any other aspects of the relationship between scientists, their organizations, the society, or the environment. Depending on the context, other ethical guidelines will also have to be taken into consideration to cover the full context of the research.

Further, the application of a scientific concept may in itself be harmful. The ethical guidelines provided here do not cover the application of true scientific concepts that may be harmful in other ways than identified here.

6 About the perspective on definitions and truth

As mentioned in the introduction to this work, even a highly influential philosophical work like “The logic of scientific discovery” by Karl Popper does not provide a set of well-defined principles for science.

The first version of this work (“10 theorems for ideas about how things work”) started out as an attempt to identify a set of principles, or methodical rules, as established by Karl Popper. That turned out to be a bit challenging, as his methodical rules were not defined and identified in a clear manner.

The following quote may shed some light on why:
“It is, I now think, the fact that most philosophers regard definitions as important, and that they have never taken my assurance seriously that I do regard them as unimportant. I neither believe that definitions can make the meaning of our words definite, nor do I think it worth bothering about whether or not we can define a term (though it may sometimes be moderately interesting that a term can be defined with the help of terms of a certain kind); for we do need undefined primitive terms in any case.”
Ref.: The logic of scientific discovery; Page 463; (Addendum, 1968)

In this work, that view is opposed by the position that definitions are of uttermost importance for an evaluation of the truth of a premise, inference or conclusion. Take for example the symbol: “+” in mathematics. Without a definition, it would just be a meaningless cross.

Even though it may seem that a definition can never be precise enough for all possible readers, the set of principles provided in this work is based on the axiom that: It is possible to define terms so precisely that a propounded statement is only open to the intended interpretation. If that is not the case for a particular statement in a particular context, a meaningful argument about that statement will not be possible.

Another issue with ´The logic of scientific discovery´ is the  perspective on truth, as illustrated by the following quotes:
“It should be noticed that a positive decision [test result] can only temporarily support the theory, for subsequent negative decision [test results] may always overthrow it. So long as theory withstands detailed and severe tests and is not superseded by another theory in the course of scientific progress, we may say that it has ‘proved its mettle’ or that it is ‘corroborated’.. by past experience. Nothing resembling inductive logic appears in the procedure here outlined. I never assume that we can argue from the truth of singular statements to the truth of theories. I never assume that by force of ‘verified’ conclusions, theories can be established as ‘true’, or even as merely ‘probable’.” 

The perspective on the term truth that has been taken in this work is that, if all definitions are in place and relevant tests have been performed, we are able to conclude if it is true that a well-defined concept really has the defined capability within a well-defined context.

Engineers will probably be familiar with this definition of truth. Engineers will be used to demonstrate the truth of their constructions – to verify and validate that a construction has a defined capability within a defined context. In particular, verify and validate are both terms that are also used in the widely used international quality standard ISO 9001.

It should be noted, however, that even though a concept can be true by the definition used in this work, another concept that has a better capability of prediction or is valid for a broader context may be eventually be discovered or invented.

By this definition, Newton´s law of universal gravitation can still be regarded to be true in the sense that the concept has a definable capability of prediction within a definable context. While Einstein´s general relativity can also be regarded to be true, but that concept has a better capability of prediction within a wider context.

It should also be noted that even if a concept is true, it can still be useless. It may be a true prediction that the precipitation at a defined location on a defined date will be between 0 and 1000 mm, but that prediction will also be of no value.

An example of this perspective on truth can be a television system. A television system can transmit a movie via a fiber and display it on a screen (whenever everything in that system performs in accordance with its design). That functionality is true – it can not be contradicted by sound argument.

It is remarkable that a lot of things have to be true for television system to work properly, more things will have to be true than an individual person can fully understand. However, even a kid can tell if it is true that it works.

This work can only be reproduced on the condition that the original source is identified by a link to https://principlesofscience.wordpress.com 

This is a thesis by ´Science or Fiction?´ with invaluable support and scrutiny by ´Gnomish´. – See how it evolved.

Revisions:
2017-09-16 Minor corrections
2017-09-17 The sections of the post was slightly rearranged by moving the bulk text from section 2 to a new section 5.

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16 thoughts on “Principles of science and ethical guidelines for scientific conduct (v8.0)

  1. ҤP7 The validation principle

    A scientific concept can only be validated by comparison of predictions deduced from that concept with measurement results.”

    Is it really that obvious that a scientific concept can only be validated by comparison of predictions with measurements?

    Maybe not – it is certainly a subject for discussion.

    However, within measurement, that is the way we validate instruments.
    Instruments can be tested by an independent test laboratory.
    The test laboratory compare the readings of that instrument (the instruments prediction of the measurand) with the independent readings of the laboratory references.

    The only things we know after the tests are:
    – the full identification of the instrument (concept)
    – the readings of the instrument (predictions)
    – the readings of the laboratory reference (observations – measurements)
    – the uncertainty of the laboratory reference (uncertainty)
    – the context of the tests (context)
    – the difference between the readings of that instrument and the laboratory reference in that context
    – wether the predictions of the instrument compare with the reference within the combined uncertainty of the reference and the stated capability of the instrument.

    Is a successful test a guarantee of the eternal truth of a concept?

    No.

    It is true that the concept passed that test, but nothing more is necessarily true about the concept.

    Are there other ways to validate a concept?

    Could be – but these other ways would have to be supported by a sound argument.

    Anyhow, this principle might deserve some discusssion.

    Like

  2. I´m not at all unfamiliar with black boxes. Actually, black boxes is what I´m used to relate to. I´m used to relate to concepts that have a claimed capability, without knowing if these concepts work in accordance with the claimed capability – or not.

    So, when does a concept become a black box? Pretty quick – I would say. It doesn´t take many inferences within a concept before we really can not know for sure if that concept works in accordance with it´s claimed capabillities or not.

    There are so many mistakes that can be made in definition of the concept, definition of the context, and definition of the capabilitites of a concept. In addition there are so many unknowns about nature. Even if it might be possible to verify that all the inferences within a concept are sound – we can not know if the predictions of that concept will correspond with observations of nature:

    «In the case of science – I think one of the things which makes it very difficult – is that it takes a lot of imagination – It´s really hard to imagine all the crazy things that things really are like!»
    – Richard Feynman

    The reasons why it is so powerful to test a concept by testing if the predictions correspond with observations -is that it kind of works for black boxes – it kind of works for complex concepts. It is impossible to adjust a concept to what isn´t known.

    However, if a concept repeatedly predicts outcomes that corresponds with observations for a defined context – the only thing we can know, is that the concept has repeatedly predicted an outcome that corresponded with observations within that defined context – in those tests.

    Anohow, science is all about sound arguments for or against a concept – not about consensus.

    Science is not about subjective levels of confidence – Science is about sound arguments for, and absence of sound arguments against a concept.

    Hence, in propounding a concept it will help to identify all sound arguments for a concept and all sound arguments against a concept that has been tested – and proven wrong. It speeds up the process.

    Whenever no more sound arguments can be voiced against a concept – we might have a working concept at our hands.

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  3. Pingback: 10 theorems for ideas about how things work | Science or fiction?

  4. the 3 axioms are the foundation of reason. it’s a thing of beauty.
    putting reason to work is what we do. why we do it is because it is consistent with our survival and the distinguishing characteristic of our nature. it is morally good.
    a scientific proposition resolves to true or false.
    if a proposition is not susceptible to this true/false evaluation then it is not reasonable (scientific)
    the principle by which a proposition is evaluated is the law of implication, if A then B.
    the ‘A’ part must specify the context of the experiment as well as the proposition being tested.
    all postulates have implications and any experiment will state an outcome of those implications and determine whether observations confirm or refute it.
    if A and then not B, then the proposition is proven to be false in the defined context.
    if A and then B is confirmed, then the truth of the proposition in the defined context has been proven.

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    • Excellent. 🙂

      I have had this vague idea that I should collect the basic logic in a separate section.

      Your comment combined with the three traditional laws of thought fits perfectly fine in that section.

      I´ll work on it.

      I´ll be away for the weekend, so I guess it will take a week or so.

      Like

      • Takes as long as it takes. 🙂

        A serf’s reading yr thoughtful guidelines with reference to Feynman’s ‘First do not
        fool yourself ‘ and ‘ If yr theory doesn’t match observation, no matter how beautiful
        it is, ( or how famous you are,) it’s wro-oong!’ (Paraphrase.) And of course, ref
        to Karl Popper regarding ad hoc adjustments or ‘theory inoculation.’

        I’ll come back and reread, thanks, Science or Fiction.

        Like

        • Thanks a lot for your feedback Beth.

          That Feynman quote is just great 🙂

          The quote from Popper that you refer to is also one of my favorites:
          “… it is always possible to find some way of evading falsification, for example by introducing ad hoc an auxiliary hypothesis, or by changing ad hoc a definition. It is even possible without logical inconsistency to adopt the position of simply refusing to acknowledge any falsifying experience whatsoever. Admittedly, scientists do not usually proceed in this way, but logically such procedure is possible» – The Logic of Scientific Discovery.

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          • Science or Fiction,
            Reading Popper , ‘Objective Knowledge’ and ‘Open Society and it’s Enemies’ was
            a seminal experience for me. And Feynman, love his curiosity and joy in discovery,
            thx for vid.

            Liked by 1 person

    • I imagine that this might be a bit too verbos for your taste. 🙂
      However, I think this might fit in imediately after the introduction, before the principles, because this puts up the background for the principles.

      The logical basis for scientific principles – and its implications

      The three traditional laws of logic

      This thesis has been founded founded on the three traditional laws of logic:

      The law of identity: a thing is itself. (For all A: A = A)

      The law of non-contradiction: A thing can not simultaneously be and not be. In other words, two or more contradictory statements cannot both be true in the same context at the same time: ¬(A∧¬A)
      (Symbols: ¬ = not ; ∧ = and )

      The law of excluded middle: Truth is a binary alternative. In accordance with the law of excluded middle or excluded third, every logically valid proposition evaluates to true or false. anything that is not true is false: A∨¬A
      (Symbol: ∨ = exclusive or )

      Reasoning and the formation of concepts

      A fundamental form of reasoning is here regarded to be a proposition on the form: If A then B.

      Realizing that the context influences on the truth of a proposition, a general form of a concept is here taken to be: A well-defined measurand B, has a well-defined relationship R with a set of well-defined measurands A within a well-defined context C.

      These three definitions are essential to that definition of a concept:
      ´concept´: any expression of a relationship between two or more measurands
      ´measurand´: a well-defined property that can be observed or quantified by a measurement
      ´context´: a set of those things that have an influence on an observed, measured or predicted value

      Expression of scientific concepts

      A more precises expression of a concept is here considered to be:
      Within a well-defined n-dimensional space, the context C, where a set of well-defined measurands: M1, M2 … Mn, are present, and each measurand has a defined property, defined value, or a value within a defined set or range of values – Then, measurand B = Mx has a well defined relationship R with a subset A = My, Mz …. of all measurands in context C.

      That definition is here considered to be a general form of a scientific concept. All scientific concepts should be possible to put on that form.

      Objectivity and repeatability

      An essential characteristic of scientific knowledge is here regarded to be that scientific knowledge must be independent from individuals. As far as a concept is supposed to be scientific, that concept should be independently verifiable.

      Then it follows that a scientific concept, and the test of it, must be repeatable. An unrepeatable observation can not possibly be independently verifiable.

      About hypothesis

      Concepts that have not been proven should be clearly identified as an ´hypothesis´: a propounded statement or concept that has not been falsified or validated.

      What is true about a hypothesis is that it is a statement or proposition that has not yet been verified or falsified. Hence, an hypothesis does not breach with ´the law of excluded middle´.

      About truth

      Ultimately, science is not about what anyone believes. Science is about invention and definition of true concepts.

      By the law of the excluded middle, If a proposition is not true, it is false. A false statement or proposition can hardly be called scientific knowledge. Knowledge must be true, else it would not be knowledge. Hence, a scientific concept must be true to deserve being called a scientific concept.

      About truth of concepts

      A scientific concept is here regarded to be true If the relationship R between measurands A and measurand B has been validated for all points in the context C, and no sound counter argument can be found against the validity of the concept, or the test of it.

      If a sound and significant counter argument can be stated against a concept, there must be something wrong with the concept.

      A definition of science

      On the basis provided so far, the fundamental view on science that is taken in this thesis is that:
      A scientific concept should be a true and independently verifiable concept that can not be contradicted by a sound argument.

      Scrutiny

      The good thing about independent scrutiny is that it helps to identify sound counter-arguments that will have to be resolved, one way or another, to arrive at a true concept that corresponds with observations within the defined context.

      Eventually one day it might be that no sound counterargument can be stated against a concept.

      The importance of scrutiny is well expressed by Karl Popper:

      “The discovery of instances which confirm a theory means very little if we have not tried, and failed, to discover refutations. For if we are uncritical we shall always find what we want: we shall look for, and find, confirmation, and we shall look away from, and not see, whatever might be dangerous to our pet theories. In this way it is only too easy to obtain what appears to be overwhelming evidence in favour of a theory which, if approached critically, would have been refuted.”
      ― Karl Popper, The Poverty of Historicism

      Technology readiness level

      How do we know that no more sound counter arguments can be found against the validity of a concept?

      Evaluation of ´Technology readiness levels´ is widely applied in industry. The highest readiness level gives a clue to when no more sound counterarguments can be found against a concept:
      Proven technology has been integrated into intended operating system. The technology has successfully operated with acceptable performance and reliability within the predefined criteria.

      It is worth noting, that a theoretical consideration alone can not prove correspondence between predicted capability and observed performance. It is impossible to reveal all possible errors by theoretical a priori considerations. Comparison between predicted capability and observed performance is required to conclude on the performance of a concept.

      The beauty of testing

      A test is a comparison of a predicted value with a reference measurement that is traceable to the definition of the measurand.

      The thing with a test, is that it is not necessary to understand the details of a concept to concluded if it passes a test or not. A non-specialist might be able tell if a concept pass a test, even though he may not be able to tell why.

      The need for independent testing

      If a concept fails a test, there most be something wrong with the concept – or the test of it. If it passes the test the concept it can be right, the test can be wrong, or both the concept and the test can be wrong.

      Unfortunately, by the existence of all those alternatives a test is non-conclusive.

      To remove suspicions of a biased test, independent testing, by a laboratory that is accredited to perform that particular test, is often demanded for critical constituents of a concept or construction.

      If a concept fails an independent test by an accredited laboratory, there must be something wrong with the concept. Or, it might come to a discussion between two independent parties about the cause of discrepancy. Anyhow the possibility for biased testing is significantly reduced.

      It still in doubt, perform another independent test, and another one. Eventually, it will be hard to put forward sound arguments for or against the test results.

      Regarding truth of a concept based on a test result

      If a concept passes one test, it can be added to the documentation of that concept that it has passed that particular test at that point.

      Regarding advanced concepts

      Advanced concepts will be a combination of concepts. Constituent concepts and their combinations must be true for a combined concept to be a true representation of what is observed.

      However, the tasks of:
      – defining the context
      – defining the measurands
      – defining the relationship
      – designing and constructing reference measurements
      – designing and performing tests that are valid for all points in the context
      – documenting every aspect of the concept
      is at best tremendous.

      An unsurmountable amount of testing might be required

      There can be a vast amount of points in a n-dimensional space. A test matrix covering all points can be enourmous.

      It can also be a huge and even impossible task to define, construct and perform tests that covers the full context for which the concept is possibly true.

      However, for each successfull test, it can be added to the documentation of the concept that it has successfully passed that test in that context at that test-point.

      Testing by observing naturally occuring events

      A concept that predicts naturally occuring measurands that develop over decades, centennials, milleniums or longer may be hard or even impossible to demonstrate within the extent of a human lifespan.

      Interpolation, extrapolation and generalization

      Interpolation between test points, extrapolation beyond test points or generalization beyond tested context are typical basis for sound counter-arguments about the truth of a concept.

      It takes a lot of verification to conclude if a concept is true as defined. Independent reviews and independent testing, are commonly used methods to counteract the corruptions of mind that so easily infects anybody who tests his own ideas.

      By this perspective, an advanced construction, like an airplane, can be thought of as a combination of many scientific concepts. No doubt, all significant definitions, reference measurements and tests must have been performed, documented and revieved for the product to be safe. However, as with all advanced constructions, we can not know for sure if a construction can or will work in accordance with definitions before the complete construction has been put to test.

      How one test can be sufficient to concluded that there is something wrong with a concept

      The thing about science, as with advanced constructions, is that it takes many specialists to design, construct and test a concept. But it may only take one independently verifiable observation of a situation where the relationsship R between measurands A and B is not true, within context C, to concluded that the concept is not true as defined, there must be something wrong with it – or the test of it.

      Sometimes, It only takes one sound argument or one observation to demonstrate that there must be something wrong with a concept.

      The space shuttle Challenger may serve as an example where one component in the construction was applied outside its validated range, and, reportedly is said to have caused its disintegration. The Mars Climate Orbiter may serve as another example, where mismatching units between design and construction is reportedly said to have caused its crash landing on Mars.

      «No amount of experimentation can ever prove me right; a single experiment can prove me wrong.» – Albert Einstein

      Summary

      All of this is probably best summarized by Richard Feynman:

      “In general we look for a new law by the following process. First we guess it. Then we compute the consequences of the guess to see what would be implied if this law that we guessed is right. Then we compare the result of the computation to nature, with experiment or experience, compare it directly with observation, to see if it works. If it disagrees with experiment it is wrong. In that simple statement lies the key to science. It does not make any difference how beautiful your guess is. It does not make any difference how smart you are, who made the guess, or what his name is – if it disagrees with experiment it is wrong. That is all there is to it.”
      – Lecture by Richard Feynman on Scientific Method (1964)

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      • nature is the great simulator that has all the parameters and infinite precision. that’s how come she’s the ultimate arbiter. she doesn’t miss a thing ever. she won’t bargain; she’ll just kill you.

        Liked by 2 people

  5. aw yiss.
    yes, verbose- kinda cute – reminds me of all the groping on my first successful mating attempt.
    practice refined the process to the point i can call it ‘fondling’ now…lol

    you have it right that a concept is a relationship – it’s also a temporal relationship with that arrow.of.implication (which, once reason has tempered it, we call ‘causality’)

    experimentation is a tool of reason, though. the validation of anything is done by reason. experiments are ways to ‘see’ those relationships and resolve the ‘gray’ to the individual black and white dots.

    i understand the nature of your emphasis, i think. it’s not wrong; just not completely sorted by significance.

    you’re almost done, friend. soon, the only thing left will be more.of.the same and extra cowbell.

    Liked by 2 people

    • Thanks – as always, it takes me some time – I realize that i will need more time to refine it.
      One thing that I wanted to do was to start with the logical basis and then look at the implications, but I messed it up a bit, so I couldn´t draw that line. I´ll pick it up again now and again and see what I can do with it.

      Liked by 1 person

    • “you have it right that a concept is a relationship – it’s also a temporal relationship with that arrow.of.implication (which, once reason has tempered it, we call ‘causality’)”

      Not elegant – but anyhow:

      Various kinds of relationships

      There are many kinds of relationships.
      A relationship can be causal, as in: 
A causes B – but B can not cause A.

      The ideal gas law is an example of a more general relationship:
      Pressure*Volume/Temperature= constant (For a given amount of gas)
      If one of the measurands is changed, and the second is kept constant, there will be a predictable change in the third.

      Like

      • time is what keeps everything from happening at once!
        it’s everywhere, always, the matrix separating events- and we exploit this to determine causality automatically.
        this is the automatic form of learning called ‘associative conditioning’ and is common to all minds.
        it can be exploited- which we call teaching.
        it can be corrupted – which we call propaganda (or worse)
        and our key distinction is that we can validate it on a meta level with logic – and reject the false relations that are contrived by exploiters or by accident. we recapitulate the formula that nature so loves. and that’s how ideas evolve – just as if they were alive. and the unfit is extinguished by submitting an idea to reason and finding it falsified.
        and when we dream, that is the exercise of our forgettery that’s busy doing just that.
        you know nature has determined that this function is worth the liability of spending 1/3 of your life in a vulnerable unconscious state?
        or, rather, nature has determined that failure to validate can be grounds for extinction- and you can get tossed into the great forgettery!

        Liked by 1 person

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