Bibliographic record
Abstract
In the Woods: Pathways of Perception is a companion piece to my MA project (a series of photographic collages of trees) which was presented as a solo exhibition at the I.M.A. Gallery in July 2012. This paper examines the disconnection between human beings and the natural environment. It argues that this disconnection is caused by the importance the Western culture accords rationality over other, more intuitive modes of perception and experience. My project aims to remedy this problem by targeting perception and reworking it through a more demanding of the audience approach in my compositions. The all-over composition of my photographic collages encourages the eyes to scan around the entire image. This scanning of the image, I strongly believe, disrupts the dominant mode of visual perception in the modem Western world, in which the figure is viewed as a distant isolated object that can be grasped immediately rather than engaged with and contemplated. I argue that this scanning attention encourages unconscious participation, allowing viewers to find their own connections and visual paths through the forest I have created. In this way the viewer is given space for contemplation and reflection; an experience that is often undervalued in our society. This paper asserts that by employing unconscious scanning attention, visual perception can be retrained, thereby destabilizing the dominant modes of thinking and experiencing. I argue that the unconscious modes of perception, intuition, and imagination play a key role in the re-connection to nature, for when we are unable to connect and empathize with the natural environment, our capacity to connect and empathize with others also diminishes. Therefore, the path towards a more ethically aware society is through the arts and the unconscious. This paper emphasizes that the desire to regard, contemplate, empathize, and love another living being, whether human or non-human, is the path towards a more peaceful, connected 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.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".