Domestic Spaces of Affection: The Role of Vernacular Architecture, Material Culture and Memory in the Cases of two Brazilian Households
Bibliographic record
Abstract
This thesis explores the role of vernacular architecture, material culture and the establishment of spatial memories in the context of domestic environments. By critically analyzing the case of two Brazilian families, one living in Brazil and one living in Canada, I argue that Brazilian domestic vernacular architecture, objects used in interior decoration and memories related to household spaces can influence affection for a place. They perform as symbols of identity and belonging, demonstrating that the sense of affection can be associated with people, objects and buildings. The houses examined in this thesis have different backgrounds: the first family lives in northeastern Brazil in a home they started to build in the 1970s. The second family immigrated to Greater Montreal in the 2010s, where they moved to a house they did not construct. Through oral interviews, I investigated the collection of emplaced memories in specific domestic environments, the entwined sense of identity and space, and how people create their domestic settings through spatial practices. In addition to interviews, the participants drew memory maps and shared vernacular photographs and personal objects that illustrate their memories related to the house. This methodology helped me in analyzing examples of spatial practice concerning both self-built domestic vernacular architecture and found domestic spaces occupied and reshaped by the family, besides tracing the affective spatial relationships in each case.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".