Social Justice in Urban Public Transportation: A User-Centric Analysis of Fares in Portoviejo, Ecuador
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective: To examine the perceptions of socially just fares among urban public bus users in Portoviejo and to assess the potential impacts of fare increases on the most vulnerable populations and the subsequent changes in their mobility behavior. Method: To unpack the multiple facets that shape the notion of justice, we conducted a two-stage clustered observational study using a survey administered to a sample of urban bus users. The data collected were scrutinized using three analytical methods: exploratory description, hypothesis testing, and binary logistic regression. Results: Our findings revealed that most bus users are women, under 35 years of age, and earn at most the minimum wage. These younger, lower-income users who utilize the bus less frequently, tend to view lower fares as just compared to their counterparts in different user profiles. When fares exceed what they perceive as just, these users tend to mitigate their bus usage, opting to walk more or invest in a bicycle or motorcycle for their daily transport needs. Conclusion: The intersection of public transport fares and social justice is not an extensively researched area, and one key theoretical challenge is balancing the principle of universal provision with users' varying payment abilities under the framework of social justice. Future research on this intersection should explore factors beyond fares, such as safety, accessibility, territorial coverage, and travel time, and consider alternative fare models to address socioeconomic disparities and improve overall well-being.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 it