Substantive research aims

Dimensions of cognitive ability

Numerous studies have found that scores on psychometric assessments of cognitive ability tend to correlate positively with each other (cf. Jensen, 1986; Ree & Earles, 1991; Spearman, 1904). Many psychologists have accepted this ‘positive manifold’ as representing a

common or general factor underlying cognitive ability (Carroll, 1993; Gottfredson, 1998;

Jensen, 1987). However, alternative explanations have also been proposed (van der Maas et al., 2006), and the phenomenon may be the result of more than one factor or process (Horn & Blankson, 2012).

The GRT2 is designed to measure three facets of general reasoning ability, rather than narrow facets or aptitudes (Psytech International Ltd., n.d). Therefore, the subscales are expected to tap into a sizable ‘common’ component, and are expected to correlate

significantly with each other. However, the correlations will not be so high as to indicate that the subscales are measuring the same construct.

Conceptualisations of intelligence tend to partition fluid (Gf) and crystallised (Gc) intelligence as separate forms or subtypes of intelligence (Horn & Cattell, 1966; Nisbett et al., 2012; Schneider & McGrew, 2012). However, Gf and Gc also correlate (Lubinski, 2004), suggesting a commonality or association between the different forms of ability. Whereas fluid

intelligence is thought to represent the most general form of reasoning ability (e.g. the ability to solve abstract and novel problems), crystallised intelligence involves the accumulation of knowledge and the use of this knowledge to solve problems. Other researchers have equated

Gf with general mental ability or g (Gustafsson, 1984; Valentin Kvist & Gustafsson, 2008). It is possible to view the GRT2 subscales in terms of fluid and crystallised intelligence. Theoretically, the abstract reasoning subscale aligns to the concept of fluid intelligence. Although the verbal and numerical reasoning subscales are designed to assess facets of general reasoning ability, these scales require learned knowledge such as the meanings of

words and rules for solving mathematical problems. The numerical and verbal reasoning subscales are conceptually closer to crystallised intelligence.

It is predicted that abstract reasoning will have the highest correlations with the other subscales, whereas verbal and numerical reasoning will correlate to a lesser extent. This prediction is based on the greater conceptual similarity between fluid intelligence and forms of

crystallised intelligence, in comparison to two distinct forms of crystallised intelligence.

• Hypothesis 1: Verbal, numerical, and abstract reasoning ability are expected to be positively related.

• Hypothesis 2: Within the range of correlations among verbal, numerical, and abstract reasoning scores, abstract reasoning will be more strongly correlated with the other subscales than the correlation between numerical and verbal

reasoning.

Cognitive ability and job performance

Research has consistently identified cognitive ability as a predictor of performance across multiple job settings (cf. McHenry et al., 1990; Olea & Ree, 1994; Ree et al., 1994;

Schmidt & Hunter, 2004), with the prediction being stronger in jobs with more complexity (Schmidt & Hunter, 1998). As identified in the literature review, the corrections officer role is associated with unique complexities, including balancing the different accountabilities of the role (e.g. security, care, rehabilitation). Based on the evidence that cognitive ability predicts performance in a range of occupational settings, it is hypothesised that reasoning abilities will

also predict overall job performance for corrections officers.

Better predictions about the relationship between cognitive ability and outcomes such as job performance can be made when looking at specific facets of the variables. Using the findings from the factor analysis about the dimensions of corrections officer performance,

relationships will be explored between each of the reasoning ability variables and the performance dimensions.

• Hypothesis 3: All reasoning ability components are expected to be associated with job performance.

• Research aim: To explore the relationships between reasoning abilities and the facets of performance for corrections officers.

Participant characteristics, ability, and performance

The research findings regarding gender differences in reasoning abilities are

inconsistent. Some studies have indicated that males are stronger in numerical reasoning and

females are stronger in verbal reasoning, whereas meta-analyses have identified that these differences are negligible (Hyde et al., 1990; Hyde & Linn, 1988). Therefore, it is predicted that any differences between male and female participants on the GRT2 subscales will be non- significant.

Other research of interest regarding the relationship of cognitive ability to gender has

found that overall reasoning ability does not vary by gender, but it may mask differences between specific abilities (Johnson & Bouchard, 2007), and that males tend to have greater variability in scores than females, particularly in the extreme high end of the scale (Hedges & Nowell, 1995). These studies suggest that there may be gender differences in terms of

cognitive ability structure, as well as variability of scores. The study will investigate the reasoning ability dimensions separately for male and female participants, including the correlations between the subscales. The study will also look at the relationship between reasoning abilities and overall job performance by gender.

• Hypothesis 4: There will be no gender difference in components of reasoning ability.

• Research aim: To explore the pattern of relationships among reasoning abilities separately for male and female participants, including correlations among verbal, numerical, and abstract reasoning.

• Research aim: To explore the relationships between reasoning abilities and overall job performance separately for male and female participants.