“Japa”: An Exploratory Study of the Roles of Social Media in an Out-Migration Trend in Nigeria
Bibliographic record
Abstract
This study seeks to understand the roles of social media in the new “Japa” migration trend in Nigeria. As part of this main objective, the study investigates the demographic characteristics of these new migrants—their age, gender, and socioeconomic status classifications. It also explores the challenges experienced by these new migrants before leaving and after arriving at their destination countries and asks if and how social media mitigates these challenges. The participants consist of Nigerians who lived in the United Kingdom ( N = 18; 48.6%), Canada ( N = 5; 13.5%), the United States ( N = 10; 27%), Sweden ( N = 1; 2.7%), and France ( N = 3; 8.1%). They were aged between 26 and 48 years, with an average age of 32.5. There were 22 (59.5%) men and 15 women (40.5%) in the study. The study finds little to no evidence to support the conclusion of a more direct influence of social media on the migration decision of this Japa migration trend among the cohort interviewed. More conservative social media platforms were preferred to other, more open social networking categories. Also crucially important is the role of trust engendered by offline social network ties (including family kinship and friendship) of online influencers. The display of affluence as a motivating factor could not be conclusively established; other factors like socioeconomic, insecurity, career prospects, and unemployment were mentioned as more important. Social media applications were recognized as information-gathering tools rather than inspirational or motivational sources for the Japa migration enterprise.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | medium |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
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 | 0.002 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".