Evaluating the motives of child labourers in the informal economy
Bibliographic record
Abstract
Purpose Conventionally, the marginalised population was considered to engage in child labour due to poverty, education or lack of other options, but indeed, a few children work voluntarily. However, a growing number of scholars, in recent years, have drawn their attention to the valuable question, “why children are engaged in child labour in the informal economy”. Even though a few studies have explored the motives of informal workers, to our knowledge not a single paper has explored the motives of child labourers working in the informal economy. The purpose of this study is to fill this gap by evaluating the motives of child labourers, through three competing theorisations of the informal economy. Design/methodology/approach In this study, face-to-face structured interviews of 45 child labourers were conducted, who worked in different automobile workshops in the city of Lahore, Pakistan. Respondents were selected using the snowball sampling technique as this strategy is suitable for researching sensitive issues and is feasible for small sample sizes. Findings The main finding is that no single explanation is universally applicable to all child labourers. Some (27 per cent) justify their participation in the informal sector as driven by necessity (structuralist perspective), majority (40 per cent) explain their participation in the informal economy as a rational economic choice (neo-liberal perspective) and finally, more than a quarter of respondents (31 per cent) engaged in child labour due to their own free will or voluntarily to work for their family (post-structuralist perspective). This study also revealed that entrepreneurial spawning is a key determinant of child labour as the majority of children, in our study, working in automobile workshops intended to start their own workshop business in the future. Research limitations/implications This article shows that children early engaged in work with entrepreneurial intention/spawning. Entrepreneurial education is very important in a child’s life. Entrepreneurial education will be a ticket to fulfill their dreams and learn new things with entrepreneurial attitude. Practical implications Government should develop the vocational training institutes for children who left the schools. Originality/value This study contributes to the body of literature by providing a better understanding of why children work in informal employment, an occupation generally perceived as constituting exploitative working conditions. This study also contributes to the wider literature of entrepreneurship by exploring “entrepreneurial spawning” as one of the major reasons underlying the participation of children in informal work.
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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 | 0.001 | 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 | 0.001 |
| 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".