The appropriation and the social implications of the mobility transition. The case of Navarra (Spain) from an international comparative perspective
Bibliographic record
Abstract
I chose to do my research on the social implications and the appropriation of the mobility transition. At first, this topic seemed to be too vast and abstract, so I needed to define a set of research objectives that would help me in focusing on my specific cases in a coherent way. The attempt to evolve towards a new mobility model was sparking debate in the city of Pamplona-Iruña. Therefore, I found it logical that my home city would be one of the case studies. We knew that suburban areas and rural areas did not face the same challenges, so I also decided to include the city´s suburban areas and a nearby rural area. Later on, I was offered the opportunity to start a collaboration with the committee of a local company, so that I could include a fourth case study (on home-work mobility) from the region of Navarra. This work would allow for the comparison of my home-region-based findings with those obtained in the foreign cities that represented different ways of managing the transition. The thesis has been divided into eleven chapters that have been arranged into three main parts. The first part of the thesis has been devoted to giving shape to a theoretical framework and to a chapter on the methodology. The second part comprises the chapters on the four international case studies that are used for a comparative analysis. The third part consists of the four chapters on the region of Navarra (Spain). I aim to offer a holistic approach to my research problem, even though covering all the social impacts of the mobility transition in advanced societies is not viable. Thus, I analyse in a comparative way a set of case studies that are meant to be representative of different types of contexts where this transition is taking place.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".