African Immigrants and Capital Conversion in the U.S Labor Market: Comparisons by Race and National Origin
Bibliographic record
Abstract
Introduction Recent scholarship on migration, international migration, and immigrants have focused on a number of geographical areas such as Africa, India, Mexico, the Caribbean, Canada, Europe, and the United States and immigration policy, capital formation, accumulation, and utilization (Cote and Erickson, 2009; de Haas, 2008; Jimenez, 2007; Athukorala, 2006; De Voretz, 2006; Chander and Thanegavalu, 2004; Jellal and Wolff, 2003; Majka and Mullan, 2002; Kposowa, 2002; Hayfron, 2001; and Dustmann, 1999). Moreover, within these studies and others, capital has been operationalized to include characteristics such as education, knowledge, language proficiency, social networks, functional or objective capital (i.e., money), and skills-set assets. However, very few studies tend to focus primarily on the differentials of capital, broadly cast, among native born African Americans, native (black) Africans, and white Africans, particularly those from sub-Saharan Africa. In fact, although the number of Africans in this country has increased from 0.4% to 3.7% of all foreign born immigrants (ACS, 2007; U.S. Census, 1999), little is known about their socio-economic achievements in the United States relative to other immigrant and native groups. This study aims to contribute to filling the lacuna in this area. We suggest that the lack of research disaggregating Africans' (white and black) performance in the labor force may have its historical roots in treating white Africans as a that has the potential to assimilate quicker that black Africans into mainstream culture by virtue of possessing a key form of capital that is highly regarded in American (U.S.) society--white skin. In fact, in classic research conducted by Duncan and Lieberson (1959) on the ecological conceptualization and immigrant assimilation in Chicago, it was found that there was a positive relationship between length of residence and assimilation for foreign-born and the second-generation from Europe. Moreover, when African Americans [Negroes at the time of the study] were added to the equation, Duncan and Liberson's (1959) findings indicated that African Americans [descendants of native Africans] did not fit the 'optimistic' patterns associated with assimilation for white Europeans. Subsequent research by Liberson (1962), Taeuber and Taeuber (1964), and Kantrowitz (1969) utilizing the Centralization Index (one of five measures of segregation) support Duncan and Liberson's (1959) contention that, Negroes are much more segregated than any immigrant group (p. 373), thus negatively affecting their overall ability for greater contacts-exchanges and economic opportunities, compromising their capital accumulation and conversion into tangible and intangible resources. Census Bureau (2002) Isolation Indices reveal a similar pattern in relation to the assimilation model, which posits that with time, groups are absorbed into the dominant culture and life chances are subsequently enhanced. When isolation measures are compared with the post-Civil War Jim Crow era, the overall levels are significantly higher today for blacks than for whites. Using the logic of the assimilationist model, since white Africans' roots are derived from European nationalities, one would expect less focus on their experiences in the United States. Although there are a sizable number of African immigrants in the United States, relatively little is known about their labor market performance (Kposowa, 2002). The few studies that exist tend to focus on one point in time (Dodoo and Takyi, 2002). Such strategy limits the ability to generalize findings or determine whether factors observed at one point of observation, for example, a single census, persist over time. Other studies combine African immigrants as one group, often failing to realize that even on the African continent, there are various racial and ethnic groups (Takougang, 2003). Combining Africans as one severely limits the ability to investigate Africans' encounter with discrimination on the basis of skin color upon arrival into the United States. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".