Feeling Poor and Lonely: The Felt Experiences of Low-Income Working Lone Mothers in Finland
Bibliographic record
Abstract
This article analyzes the current feelings of Finnish low-income working lone mothers and their views on what it means to be poor in the welfare state of Finland. This is done by analyzing written accounts of lone mothers through a qualitative content analysis. The data was collected in 2015 and 2021. The analysis reveals that mothers’ feelings of poverty have similarities to those described in data collected in a different context over 20 years ago. The article is inspired by an article published in Affilia in the year 2003 by Lynn McIntyre, Suzanne Officer, and Lynne M. Robinson. In their paper, McIntyre et al. analyzed the feelings of poor Canadian lone mothers. While the welfare regime and services influence how life is organized, it is evident that self-sacrifice for the children caused by poverty is very much a part of the written accounts of Finnish mothers. We show that while there are a few cultural differences in the feelings that lone mothers undergo on account of their low-income status, feelings such as loneliness are persistent and often shared regardless of time or geographical location. Therefore, we suggest that low-income mothers should be given greater support by society and governments to be able to feel hopeful and empowered rather than poor and alone.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".