Questioning the role of information poverty in immigrant employment acquisition: empirical evidence from African immigrants in Canada
Bibliographic record
Abstract
Purpose Skilled, well-educated African immigrants arrive in Canada with aspirations for more opportunities and a better life, but too often end up with few employment options and precarious jobs. The purpose of this paper is to investigate the experiences of African immigrants attempting to locate suitable, well-compensated employment in Canada. More specifically, this paper reveals how long-standing information poverty frameworks from the field of information behavior are inadequate for understanding intersectional and broader socio-cultural forces influence access to information and employment precarity among African immigrants. Design/methodology/approach Data were collected through semi-structured interviews with twenty-five African immigrants in Metro Vancouver. Qualitative content analysis was used to explore participants' employment information seeking and perceptions of information availability using Britz's information poverty framework. Findings Participants encountered a range of difficulties when seeking information related to employment, including content, process and identity-related challenges, in alignment with Britz's framework. However, the framework did not fully encompass their information seeking experiences. Limited access to relevant information impacted participants' ability to make timely career decisions, and there was evidence of information inequity resulting from a mismatch between information provision and participants' multifaceted identities. Originality/value This research applied Britz's information poverty approaches and provided a map of participants' responses to information seeking challenges. Participants did not fit into the category of information poor as defined by Britz. The findings suggest that the discourse on information poverty would benefit from considerations of the diverse backgrounds of information seekers and the incorporation of cultural dimensions to understandings of information access, information poverty and technology use for information seeking.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.024 | 0.014 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".