Hookless : an exploration of eco-tourism based architecture seen through Fishing, causing new consideration of our design process and role as Architects
Bibliographic record
Abstract
Remote Architecture, in the form of eco-tourism lodging, is a direct touchpoint for architecture and occupants, and how these two forces work together to interact with nature. Eco tourism throughout history has been both beneficial, and detrimental, to our natural world. This thesis strives to focus on the architecture of remote lodging, and how it inspires occupant interaction with nature. The strong suspicion of this project is that tangible architectural moves, styles, and interventions, greatly affect occupant interaction with surrounding nature. Therefore, architecture can help influence more positive, conservation minded interaction, in place of extractive and exploitive tourism tactics. An exploration of the eco-tourism space, and existing architecture will identify common typologies and compare how these typologies affect occupant interaction with surrounding nature. A re-understanding of these typologies based on the interaction they inspire will help to distinguish and define ‘positive’ and ‘negative’ practices in eco tourism architecture. Finally, the findings will be translated into design and site considerations vital to positive, sustainable eco-tourism achieved through architecture and design.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".