【正文】 otypes for three occupations (engineer, accountant, and elementary school teacher). These occupations represented the end points and middle of a masculinefeminine continuum of explicit occupationsex stereotypes. Implicit stereotypes were assessed using the Implicit Association Test (IAT), which is believed to minimize selfpresentational biases mon with explicit measures of occupationsex stereotypes. IAT results for the most gender stereotyped occupations, engineer (masculine) and elementary school teacher (feminine), were parable to explicit ratings. There was less agreement with less stereotyped parisons. Results indicated that accounting was implicitly perceived as more masculine than explicit measures indicate, which calls into question reports of diminishing gender stereotyping for such occupations.Keywords Occupationsex stereotypes .Implicit stereotypes .Stereotypes .Implicit Association TestPopular beliefs have long held that because of their stereotyped traits and temperaments men and women are suited for different kinds of occupations. One of the earliest empirical examinations of these occupationsex stereotypes was conducted by Shinar (1975) who showed that college students thought that some occupations required masculine traits, while others required feminine traits. The method that Shinar (1975) and others (Beggs amp。Doolittle, 1993。s (1992) effect size, d, in that the differences between IAT test steps or blocks are standardized by their pooled standard deviation. All responses in the two test blocks were considered for these calculations. Trials with latencies greater than 10,000 ms and participants with more than 10% of responses 300 ms or less were eliminated. Block means of the remaining trial response latencies and standard deviations for the pooled test block latencies were calculated. These means, plus 600 ms, replaced error latencies. Differences between block means, with error replacement, were then divided by the pooled standard deviation, without error replacement. The resulting D values are reported in Table 1 .These data are grouped by three target occupation parisons (., engineer vs. accountant). Each target occupation is further defined by the gender presentation order of the job target (., male engineer vs. female accountant contrasted with female engineer vs. male accountant).The influence of these variables (target occupation pairs ,gender stereotype congruency presentation order) was examined in a twoway ANOVA with D serving as the dependent variable. The main effect for target occupations was significant F (2, 150)=, p.00l. As anticipated, the engineeraccountant IAT parison was significantly smaller (N1=, SD=) than the other two parisons based on Tukey39。事實上，這種方法最早是由Katz和Braly（1935）用于他們非常早期的關(guān)于國民刻板印象的工作中?？赡芸贪逵∠筮@樣的認(rèn)知偏見存在并持續(xù)影響內(nèi)隱水平，即使他們不是出現(xiàn)在一個外顯的水平(Kundaamp。相比之下，職業(yè)性別刻板印象明顯的特征是用熟悉的李克特量表進(jìn)行評估。 Cejka amp。同學(xué)們表達(dá)了他們下列的種族劃分觀念：白種美國人（%）、非洲美國人（%）、亞洲美國人（%）、本土美國人（%）、拉美美國人（%）和其他（%）。假設(shè)第一個名字是“馬修”，正確的回答是按左鍵。該程序最后的屏幕是一句感謝你們的幫忙的話語，實驗者詢問被試測驗情況，感謝他們，給他們參與研究的課程學(xué)分。這些方法加上600毫秒，就能夠代替錯誤的潛在因素。在1975年，,，每一種手段測量都有顯著不同。沒有其他的對比組是有效地。20。這個職業(yè)的外顯等級經(jīng)常被展示為中性職業(yè)(Beggsamp。在內(nèi)隱方法測量地情況下，最初的分?jǐn)?shù)是來自文本框1。結(jié)果D的價值標(biāo)準(zhǔn)在文本框一中顯示，這些數(shù)據(jù)有三個目標(biāo)職業(yè)的對比組成（比如：工程師和會計師的對比）。呈現(xiàn)合適的刻板的工程師男性組合（小學(xué)老師女性組合）比呈現(xiàn)刻板的不一致的工程師女性組合（小學(xué)老師男性組合）有更快的反應(yīng)，這意味著工程師男性組合比工程師女性組合有更強(qiáng)的聯(lián)系和更容易取回。第三步是將第一和第二步結(jié)合起來，從而使得一個反應(yīng)鍵能夠分享。學(xué)生能夠掙得額外的學(xué)分，根據(jù)計劃參與研究的學(xué)分由他們分別的進(jìn)程老師來核準(zhǔn)。 White et al., 1989)。比如，護(hù)士一貫被列入女性職業(yè)中(White et al., 1989)。一個用于描述內(nèi)隱刻板印象和其他內(nèi)隱認(rèn)知的策略是由內(nèi)隱聯(lián)想測驗所提供(IAT。大多數(shù)概念性治療的刻板印象,所有流行的帳戶,都強(qiáng)調(diào)這些外顯的過程及其內(nèi)容。s (1975) participants rated engineer as on the 7point scale, while participants of both White et al. (1989) and those from the current study rated it as approximately . Accountant was rated as in 1975, in 1989, and in 2003. Each of these means is significantly different from each other.Implicit and Explicit MeasuresCorrelations among implicit and explicit measures are shown in Table 3. All of these correlations are based on difference scores. In the case of the implicit measures, these are the scores originally shown in Table 1 .A positive value reflects a preference for the gender stereotypic parison pair, ., male engineer and female elementary school teacher. Explicit scores reflect the absolute value of the difference between each of the three pairs on the masculinityfemininity scale. A higher score implies greater gender stereotyping for two occupations. Correlations among explicit scores indicate that participants who stereotyped engineers and elementary school teachers also stereotyped accountants and elementary school teachers, , p. was a similar positive correlation between scores on the engineerelementary school teacher and the engineeraccountant parisons, , p. contrast, stereotyping scores on the engineeraccountant parison were inversely associated with stereotyping scores on the accountant elementary school teacher parison , , p . well be recalled, implicit scores for different occupation parisons were drawn from different participant groups. Correlations across the different IAT parisons were accordingly not possible. Nonetheless, Table 3 shows the correlations between each participant group39。Eagly, 1999。 Whito, Kruczok, Brown,amp。s answer. Further, the strength of this effect will be influenced by the strength of the preexisting stereotype. If the stereotype is strong or well established, the effect will be larger. If it is weak, the effec