Barriers to citizen participation: the missing voices of people living with low income
Bibliographic record
Abstract
This article reflects the involvement of people living with low income in the discourse and decision-making on issues related to poverty. It reports on the process and outcomes of a 1-year project, developed by KAIROS1 aimed at identifying tools, strategies, and policies to increase the participation and engagement of people living in poverty in order to help reduce and eliminate poverty in Canada. It presents the reflections, analysis, and recommendations of 55 project participants from Charlottetown, Montreal, and Victoria – a large, a medium-sized, and a small city, respectively, in Canada. It highlights the use of learning circles as one approach to enhance citizen participation in policy development albeit with limitations of time, funding, and broad impact. It concludes by calling for: (i) an increase in local learning and action opportunities for people living in poverty; (ii) more supportive front-line interactions between governmental and non-governmental agencies and people living on low incomes; (iii) government policy initiatives to reduce poverty; and (iv) action to increase public understanding of poverty to reduce the stigmatization of, and discrimination against, people living in poverty.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.031 | 0.019 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".