African-American and Anglo Anglers' Attitudes toward the Catch-Related Aspects of Fishing

Abstract

Race and ethnic differences with respect to catch and harvest related attitudes are poorly known. Based on previous research, African Americans and Anglos were expected to differ with respect to importance attached to four constructs related to the catch-related aspects of recreational fishing: catching something, catching a lot of fish, catching large fish, and retaining fish. Four Texas statewide angler surveys conducted from 1989–1997 were used to explore possible differences between African-American and Anglo males on the four catch-related constructs. Meta-analysis techniques were used to determine treatment by study interactions and provided a weighted average effect size. African Americans had stronger attitudes toward catching large numbers of fish, catching large fish, and retaining the fish they catch than Anglos. African Americans and Anglos did not differ on the catching something construct. Results supported subcultural theory explaining differences in attitudes between race and ethnic groups. Group differences were useful for better understanding consumptive behavior and environmental justice.

Keywords:

• race
• ethnicity
• catch-related attitudes
• recreational fishing
• meta-analysis

We appreciate the funding support of the Texas Agricultural Experiment Station and the Fisheries Division of Texas Parks and Wildlife for the data collection efforts relied on in this research. Additional grant support provided by the Race and Ethnic Studies Institute at Texas A&M University was instrumental to this project and is recognized. We thank each of the graduate and undergraduate students in the TAMU Human Dimensions Lab involved in completing the four statewide angler surveys (1989–1997). Finally, we appreciate the helpful review comments provided by James McNamara, Alex McIntosh, Robert D. Brown, two anonymous reviewers of this article, as well as those of the editor.

Notes

1. Using each group's average score and its standard deviation on each of the measurement scales, an Effect Size (Cohen, 1969; Glass, McGaw, & Smith, 1981), denoted by g, was calculated using the observed sample mean difference as the numerator, and the pooled standard deviation as the denominator. Because g is a slightly biased estimate of the population effect size (δ), tending to overestimate it for small samples, a slight correction for g presented by Hedges (1981) provides an unbiased estimate, d, of g. The variance of d (v _i ), the reciprocal of the variance (w _i ), and resultant w _i d _i , and w_id_i ² were calculated for use in the meta-analysis of the data. Meta-analysis techniques (Hedges & Olkin, 1985) were used to test whether effect size estimates were homogenous over the four studies (i.e., vary only by unsystematic sampling error) using a Chi-square goodness of fit test [Equation (1)] and comparing the value obtained to the critical χ² value for the appropriate degrees of freedom (3 in this case):

• (1)

If studies were homogenous (indicating no treatment by study interactions) a weighted average effect size was computed by weighting each study's individual effect size estimate by the inverse of its variance due to sampling error using the following equation:

• (2)

This test is conceptually a test for the “main effect” of ethnicity across studies. This weighted average effect size has a variance of:

• (3)

Finally, a corresponding 95% confidence interval was computed around the weighted average effect sizes to determine if they were statistically significant. For all constructs, effect sizes were computed with African Americans as the leading mean in the equation. A positive weighted average effect size whose 95% confidence interval did not include zero indicated a significant difference (p < .05 level favoring African-American males). Conversely, a negative weighted average effect size whose 95% confidence interval did not include zero indicated a significant difference favoring Anglo males. The effect size allows one to express sample mean differences in standard deviation units, and allows an effect size indicator to be interpreted using a normal distribution. Hence, a percentage difference can be determined (McNamara, 1992).

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