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Spearman's hypothesis

Spearman's hypothesis is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Spearman's hypothesis rather than just read about it. In short: Spearman's hypothesis is a conjecture that has played a historical role in debates surrounding race and intelligence. Its original formulation was that the magnitudes of black–white differences on tests of cognitive ability positively correlate with the tests' g-loading.

Key takeaways

  • Spearman's hypothesis belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Spearman's hypothesis to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Spearman's hypothesis from memory before moving on to harder problems.

Reference excerpt

Spearman's hypothesis is a conjecture that has played a historical role in debates surrounding race and intelligence. Its original formulation was that the magnitudes of black–white differences on tests of cognitive ability positively correlate with the tests' g-loading. The subsequent formulation was that the magnitude of black–white difference on tests of cognitive ability is entirely or mainly a function of the extent to which a test measures general mental ability, or g. Spearman's hypothesis has been criticized by scientists on both methodological and empirical grounds. Historically, it has been used to support racial pseudoscience.

Description The hypothesis, first formalized by Arthur Jensen in the 1980s based on Charles Spearman's earlier comments on the topic, stated that the magnitude of the differences is directly related to the magnitude of the g-loadings of a test. Jensen devised the method of correlated vectors (MCV) to study this hypothesis and published his research in his paper, "The nature of the black–white difference on various psychometric tests: Spearman's hypothesis", a paper which elicited 29 comments from experts in the field. Jensen went on to argue that the finding of a positive correlation between group differences and g-loadings would support the hypothesis that the group differences were largely in general mental ability—the later formulation of Spearman's hypothesis. The validity of this inference has been much debated.

Related hypotheses

Group differences Closely related to Spearman's hypothesis is the hypothesis that the magnitude of certain group differences correlates with within-group heritability estimates. Arthur Jensen and J. Phillippe Rushton, for example, reported in 2010 that the found psychometric meta-analytic correlation between g-loadings and heritability estimates was 1. The international data, though, has challenged this finding: a study from Japan published in 2014 did find a correlation between g-loading and heritability, but only a third of that found by Jensen & Rushton; one from 2015 covering Korea that found no clear link between heritability and g-loadings of IQ subtests; and one from 2016 by Voronin, Te Nijenhuis, and Malykh found negative correlations between g-loadings and heritability in two samples of Russian twins.

Criticism Spearman's hypothesis has often been taken to imply natural differences in black–white general intelligence, a conclusion that is rejected by a strong consensus within the scientific community. Historically, it has been used to justify pseudo-scientific racist theories. Spearman's hypothesis and the arguments that invoke it have received multiple criticisms, including criticisms of Jensen's method of correlated vectors, of the inference that the first formulation of Spearman's hypothesis supports the second, and of genetic and biological arguments made on the basis of Spearman's hypothesis. First, Jensen's MCV has been criticized with regards to the original formulation of Spearman's hypothesis. Peter Schönemann and others argue that MCV produces tautological results; Schönemann further notes that Jensen's summary of Spearman's hypothesis is vaguely defined and essentially presents two contradictory interpretations. Dolan and Lubke (2001) find Schönemann's argument that the correlations are positive by mathematical necessity unconvincing; however, they agree with his broader concern about whether his correlations are a good test of the role of g in racial intelligence differences. Ashton and Lee (2005) argue that MCV can produce spurious results. Second, Jensen's MCV has been criticized with regards to the claim that it supports the later formulation of Spearman's hypothesis. Dolan et al. (2004) argue that MCV lacks specificity: that is, that instances not including g differences could create a positive correlation between the magnitude of the group differences and the g-loadings. Dolan et al. (2004) note that they are specifically criticizing MCV as a way of proving that group differences largely or totally represent g differences; they don't argue against Spearman's hypothesis as originally formulated and they do not argue that the larger body of evidence does not support Spearman's hypothesis as later formulated. Hunt and Carlson summarize criticism:

The essence of these objections is that the method of correlated vectors does not consider alternative hypotheses concerning the latent traits that might give rise to the observed difference in test scores. When a more appropriate method of analysis, multigroup confirmatory factor analysis, is applied, it has been found that Spearman's hypothesis (i.e., that the difference is due to differences in general intelligence) is only one of several models that could give rise to the observed distributions in test scores (Dolan, 2000). These findings render the method of correlated vectors ambiguous—which is not the same as saying that the Jensen-Rushton position is incorrect. Our point is that the argument for the default hypothesis is an indirect one. It would be far better if a direct causal argument could be made linking racial/ethnic genetic differences to studies of the development of the brain.Third, arguments based on Spearman's hypothesis have been criticized. Some have argued that culturally caused differences could produce a correlation between g-loadings and group differences. Flynn (2010) has criticized the basic assumption that confirmation of Spearman's hypothesis would support a partially genetic explanation for IQ differences. He argues that environmental causes for average group IQ differences would cause the differences to be greater for more complex tasks.

References

Worked examples

Example 1 — a first encounter with Spearman's hypothesis

Start with the simplest possible case. Write down what Spearman's hypothesis claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Spearman's hypothesis before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Spearman's hypothesis ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Spearman's hypothesis

In research
Spearman's hypothesis appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Spearman's hypothesis in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Spearman's hypothesis is common in secondary-school and first-year university syllabi. It links to neighbouring topics Race and intelligence controversy, so understanding it makes those chapters shorter.
In everyday life
Look for Spearman's hypothesis outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Spearman's hypothesis in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Spearman's hypothesis means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Spearman's hypothesis out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Spearman's hypothesis in simple terms?

Spearman's hypothesis is a conjecture that has played a historical role in debates surrounding race and intelligence. Its original formulation was that the magnitudes of black–white differences on tests of cognitive ability positively correlate with the tests' g-loading.

Why does Spearman's hypothesis matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Spearman's hypothesis?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Spearman's hypothesis.

Tags

  • Race and intelligence controversy

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