From Measurement to Testing the Theory of Human Constants

Introduction

Measurement is a necessary step for transforming theoretical concepts into observable variables; however, measurement alone does not test a theory. A theory enters the stage of empirical testing when statements and hypotheses are derived from its concepts and indicators that can be verified, refuted, or revised with real data.

In the Theory of Human Constants, this path is of special importance because the four constants of survival, connection, meaning, and order are broad and multidimensional concepts, and their theoretical value is most revealed in the relationships among them and the dynamics of these relationships.

1. The Difference Between Measurement and Testing

Measurement answers: "How should the state of a phenomenon be measured?"

Theory testing raises a different question:

"Are the relationships among phenomena that the theory predicts observed in real data?"

Therefore, an indicator may be well constructed, but still have not tested any theoretical statement.

2. Beginning Testing From Theoretical Statement

Testing must begin from theory itself.

For example, if the theory suggests that severe disruption in one of the four constants can be transmitted to other domains, this statement must be transformed into an empirical hypothesis.

In this case, one can examine whether such transmission is observed in real societies.

3. Transforming Statement Into Hypothesis

A hypothesis must be clear, specific, and testable.

For example:

"Severe increase in economic insecurity is accompanied by declining social trust."

This statement can be examined empirically.

However, to test it, it must be specified how economic insecurity is measured, how social trust is measured, and what other factors must be controlled.

4. Hypotheses About Relationships Among Constants

An important part of the program for testing the theory should be dedicated to relationships among the four constants.

For example, one can design hypotheses about the following relationships:

Survival ← Connection

Connection ← Order

Meaning ← Order

Order ← Survival

and two-way relationships among them.

The goal is not to assume the direction of all relationships from the beginning, but rather to design specific and testable relationships based on theory and existing evidence.

5. Hypotheses About Imbalance

Another hypothesis can concern imbalance.

For example:

"Disproportionate increase in the capacity of one domain, under specific conditions, is accompanied by increased pressure on other domains."

This hypothesis requires precise definitions of "disproportionate," "capacity," and "pressure."

Without these definitions, the statement remains merely a theoretical assertion.

6. Hypotheses About Regulatory Capacity

One of the more important hypotheses can be:

"Societies with higher regulatory capacity show less disruption in overall functioning in response to similar shocks."

Here the researcher must first operationalize regulatory capacity and then compare the functioning of societies before and after the shock.

7. Comparative Testing

One suitable method is comparison of multiple societies.

If societies with relatively similar conditions show different results in response to a similar shock, one can examine whether differences in the structure of the four constants or in regulatory capacity can explain part of this difference.

This method can help identify effective variables.

8. Longitudinal Testing

Testing at a single point in time is not sufficient for studying the dynamics of the four constants.

Longitudinal data enable examining changes over time.

For example, one can examine whether change in survival preceded change in connection or vice versa, and whether these changes ultimately led to change in order or meaning.

9. Pre- and Post-Crisis Testing

Crises provide suitable situations for testing theoretical relationships.

The researcher can compare three periods:

Before crisis → During crisis → After crisis

Within this framework, one can examine changes in the four constants, intensity of disruption, speed of response, and degree of reconstruction.

10. The Importance of Baseline

To assess the impact of a crisis, the pre-crisis condition must be specified.

If the baseline condition is not measured, determining the degree of change will be difficult.

Therefore, in longitudinal studies, establishing a baseline for each variable is of great importance.

11. Controlling Rival Variables

The observed change in one constant may be the result of other factors.

For example, declining social trust may not only result from declining economic security; factors such as war, political change, media, migration, or cultural transformation may also be influential.

Therefore, testing the theory must attempt to the extent possible to identify and control for rival variables.

12. Correlation and Causality

One of the most important principles of empirical testing is that correlation does not mean causality.

If two variables change simultaneously, one cannot yet conclude that one causes the other.

In the Theory of Human Constants, this issue is even more important because the four constants can affect each other in two-way fashion.

13. Reciprocal Causality

For example, survival can affect connection and connection can also affect survival.

Social cooperation can better distribute resources and better access to resources can increase the basis for cooperation.

Therefore, testing models should, where possible, consider reciprocal relationships.

14. Time Lag

The effect of a change may not appear immediately.

An economic crisis may begin today, but the decline in social trust or political changes may become apparent years later.

Therefore, theory testing must consider the possibility of time lags among changes in the four constants.

15. Non-linear Relationships

The effect of one variable may increase up to a certain level and then change.

For example, an increase in order can initially increase coordination, but after a certain point flexibility may decrease.

Therefore, empirical testing should not assume from the start that all relationships are linear.

16. Thresholds

Some changes may have limited consequences until reaching a critical point.

After passing that point, changes can become very rapid.

If such a pattern is observed in the data, it can be important for developing the concept of "threshold" in the Theory of Human Constants.

17. Predictive Testing

One of the strongest tests is when the theory can provide a specific prediction before observing the outcome.

For example, if the theory predicts that severe increase in imbalance among the four constants increases the probability of crisis, the indicator of imbalance should be measured before the crisis occurs.

This method is stronger than merely retrospective interpretation.

18. Out-of-Sample Testing

If a pattern is discovered with initial data, it is better not to use those same data to conclusively prove it.

One can build the theory or model with part of the data and then test it on different data that were not used in building the model.

This helps examine generalizability.

19. Testing in Different Societies

If the theory makes universal claims about human tendencies, it must be tested in different societies.

Testing in one country or one culture alone cannot prove claims about all human societies.

Cultural and historical diversity must be part of research design.

20. Historical Testing

History can also be a context for testing the theory.

However, in historical studies, one must be careful about selective choice of evidence.

The researcher should not choose only events that are consistent with the theory.

Inconsistent evidence must also be recorded and analyzed.

21. Testing Theory Against Rival Theories

A theory gains greater strength when it can also show adequate performance in comparison with rival theories.

For example, if the Theory of Human Constants explains a social crisis, it should be examined whether its explanation provides more information compared to purely economic, political, institutional, or cultural accounts.

22. The Criterion of Explanatory Power

Explanatory power does not depend only on the number of phenomena that the theory can address.

The theory must be able to explain specific relationships and show why a result occurred under particular conditions.

If the theory can explain any result after it occurs with reference to one of the four constants, its testability is reduced.

23. The Danger of Confirmation Bias

One of the important dangers for any new theory is the researcher's tendency to find confirming evidence.

To reduce this danger, it must be clear from the beginning what evidence can confirm, weaken, or refute the hypothesis.

The existence of refutability criteria is of fundamental importance for scientific development of theory.

24. Revision of Theory Based on Evidence

The goal of scientific testing is not eternal proof of the theory.

If data are inconsistent with a hypothesis, it should be examined whether the problem is in the definition of concepts, indicators, measurement methods, or the hypothesis itself.

If necessary, the theory must be revised.

Revisability is one of the important conditions for the maturation of a theoretical framework.

25. Program for Testing the Theory of Human Constants

The path of testing the theory can be summarized as follows:

1. Defining concepts

2. Operational definition

3. Determining dimensions

4. Selecting indicators

5. Designing hypotheses

6. Data collection

7. Selection of analytical method

8. Testing relationships

9. Comparison with rival theories

10. Testing in other samples and conditions

11. Examining inconsistent cases

12. Revision or strengthening of theory

This path can move the Theory of Human Constants from the level of a conceptual framework to a cumulative and evaluable research program.

Conclusion

The distance between "measurement" and "testing" is the distance between measuring reality and evaluating a theoretical statement.

In the Theory of Human Constants, measurement of the four constants is a necessary phase; but the determining phase begins when relationships among survival, connection, meaning, and order are transformed into specific hypotheses and these hypotheses are tested in real data, across different times and societies, and in comparison with rival accounts.

Theory will gain greater scientific power when it can explain not only consistent cases but also inconsistent ones, and when it has the capacity for revision in face of new evidence.

Therefore, testing the Theory of Human Constants should not be designed with the goal of proving a prior theory; rather, it should be conducted with the goal of discovering the degree of theory's fit with reality and identifying its strengths and weaknesses.

Key sentence: "The Theory of Human Constants moves from a conceptual framework toward a researchable theory when it transforms relationships among survival, connection, meaning, and order into specific hypotheses and tests them against real data, rival theories, and inconsistent evidence."