‘Doing’ capital: examining the relationship between immigrants’ occupational engagement and symbolic capital
Bibliographic record
Abstract
Globalization has enabled greater mobility and social change through the expansion and diversification of international migration. Following immigration, people become embedded within varying fields of practice. Within these fields, which have been described as social spaces or settings (e.g. workplace) that are characterized by particular norms, certain forms of capital including language skills or educational credentials may be more highly valued than others (Bourdieu 1977; Moore 2008; Thomson 2008). The purpose of this paper is to illustrate how the differential value of immigrants’ symbolic capital within the host societies’ fields influenced their engagement in daily occupations and shaped their socio-economic integration. It is argued that the misrecognition of capital contributes to symbolic violence experienced by immigrants who must subsequently engage in a range of occupations in order to regain forms of symbolic capital that are lost and devalued following immigration. A study was conducted with a multinational group of immigrants in London, Ontario, Canada and Auckland, New Zealand, using narrative and visual methods. Data analysis adopted a theoretical framework informed by concepts from Bourdieu’s theory of practice (1977, 1990). Results illustrate a reciprocal relationship between occupation and symbolic capital, whereby recognition of the latter facilitated immigrants’ everyday ‘doing’. Conversely, the devaluing of capital led many to attempt to acquire resources that could enable their opportunities within specific fields. These findings contribute to the literature on critical understandings of capital as shaped by social power relations, highlighting ways that misrecognition of capital contributes to symbolic violence in processes of socio-economic integration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".