Repair and re-shop: an experiential approach to second-hand retail
Bibliographic record
Abstract
The rapid advancement of technology, coupled with the onset of the unprecedented 2020 COVID-19 pandemic and the escalating climate crisis, has significantly reshaped shopping experiences and consumer values. These changes have led to a rise in the popularity of online platforms and a decline in activity within physical stores. Additionally, there is also a growing interest in sustainable alternatives, such as second-hand markets, in response to anti-waste efforts. This shift in consumer values highlights the need to reconsider the role of physical second-hand stores to ensure their continued relevance in today’s digitally integrated retail landscape. This Master of Interior Design practicum explores the potential of an experiential retail approach to second-hand stores. Specifically, it proposes a remodelling of the former Singer Sewing Machine Building at 424 Portage Ave in Winnipeg, Manitoba, by applying repair and reuse practices. The project utilizes research methodologies, including literary analysis, precedent study, site and building analysis, and a visual essay to inform the creation of an interior that caters to consumer desires for engaging experiences and values of sustainability. It draws from concepts including experiential retail, adaptive reuse, and branding to enhance users’ experience by providing opportunities to learn, interact, and share knowledge around the notion of circularity. Ultimately, this project shifts the focus from creating spaces just for transactional encounters to environments for recreational, educational, and sustainable activities to occur, thereby transforming the role of second-hand stores in the digital age.
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.024 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".