{Re} Programa. (Re)habitation + (Re)generation + (Re)programming. The recycling and the sustainable management of the Andalusian housing stock. Management of habitable surroundings from the criteria of active aging, gender and urban habitability.
Bibliographic record
Abstract
The imminent socioeconomic situation of crisis which we face will have the double image of obsolescence: that of the population and that of residential buildings in which they live. In this fi rst quarter of the 21st century, there is a large percentage of homes in the residential housing stock which have not been adapted to the housing standards demanded by regulations, and which are in need of urgent rehabilitation. The limited economic capacity of older people, mainly women, hinders the fi nancing of rehabilitation, improvement or refunctioning work on the buildings where they live. It is foreseen that, in the future, public administrations will not have suffi cient resources to implement funding policies for residential rehabilitation, or for increasing the specialised housing stock to respond to the foreseeable demand in the medium to long term. In (Re)Programa, we have designed tools and management strategies which allow these social groups, in situations of physical and economic vulnerability, to undertake works for the recycling, rehabilitation and adaptation of architectural and urban spaces, in a sustainable manner, limiting the negative environmental, social and economic impacts. This publication presents the main results of the research project.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.187 | 0.084 |
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".