The adaptability of public space in Mexico City after an earthquake: a preliminary classification
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
marked the 30th anniversary of the Mexico City earthquake in which thousands of people died and hundreds of buildings collapsed. During this disaster, public space played an extremely important role not only in the emergency phase but also in the reconstruction phase; streets and squares were used not only as shelter but also as strategic points for the collection of food and organization for reconstruction works. By being in a seismic risk zone, it is of utmost importance to assess the location, characteristics, and current situation of public space in Mexico City, as public space will be a crucial resource in an emergency both during and after a disaster of this dimension. Therefore, the results of a preliminary assessment of public spaces in Mexico City are presented here to answer two main questions. What and which characteristics had the public spaces used during and after the 1985 earthquake and what is the present state of these public spaces? Results show that although seismic risk persists, public space has diminished in terms of quality and quantity toward two trends. First, some spaces have been privatized and have been replaced by shopping malls, and secondly, other spaces are saturated with new buildings in and around public spaces. From this, we can conclude that the role of public space in relation to disaster has been demerited over the years, which reduces the possibilities of recovery in the aftermath after an earthquake. Therefore, urban policies and impact studies for new projects should reconsider the role that public space may play in case of a disaster in one of the most populated cities in the world.
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 | 0.001 | 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 | 0.000 |
| 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