The (d)evolution of a technological species: A history and critique of ecopsychology's constructions of science and technology
Bibliographic record
Abstract
In this paper, I aim to convey the history of ecopsychology's changing conceptualizations of science and technology and their role in facilitating engagement with the ecology movement. To do so, I compare ecopsychology's treatment of science and technology in two important publications: Gatherings, a non-peer-reviewed digital journal of the early 2000s that portrayed ecopsychology in humanistic, socially critical, and artistic terms; and Ecopsychology, a scholarly journal founded in 2009 that regarded ecopsychological questions as testable hypotheses, and distinguished itself from prior ("first generation") ecopsychology on the basis of its embrace of technological progress and the scientific method. As a part of this shift, ecopsychologists of the "second generation" championed the notion that humans are a "Technological Species," an ontological statement that naturalized the increasing sophistication of high technology as the result of inherent human drives, and established conceptual groundwork for studies that used consumer technology such as computers to mediate experiences of nature. In the final part of the paper, I critique the "Technological Species" proposition for obscuring the historical and material conditions that make the existence of consumer technology possible, such as the ecologically devastating mining of rare-earth metals on colonized land in Central and South America. I argue that, to be socially and ecologically accountable, ecopsychology should turn toward practices that help us make sense of consumer technology's place in systems of colonialist and ecological violence, process our place within these systems as users of consumer technology, and build community less dependent on technology.
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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.140 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".