Re-Imagining The Antarctic Treaty: Goals to Mitigate Ice Melting, Reduction of Zooplankton Communities, and Imbalances In the Arctic Ecosystem
Bibliographic record
Abstract
In 2022, massive ice melts in Antarctica and Greenland reflect the human-induced impacts of climate change, and the necessity of using human solutions to respond to the global climate crisis. Although the current Antarctic Treaty characterizes Antarctica as a place of scientific reserve, it does not address the direct impacts of climate change on the cryosphere. Due to the growing mortality rate of the arctic zooplankton and their essentiality within the arctic food chain, this study proposes an “Emergency Antarctic Climate Treaty Protocol” that presents the effects of climate change on the Antarctic ecosystem as an “emergency.” To better examine the correlation between ecosystems and human systems within the context of climate change, this research project asks: 1) How does characterizing the arctic zooplankton community as a “vulnerable species” address its essentiality to the arctic food chain? 2) What is the correlation between disruptive impacts to the arctic biosphere and negative impacts on human communities? 3) What role does the “Emergency Antarctic Climate Treaty Protocol” play in addressing the necessity of integrating emergency climate discourse into ice melt trends in the Antarctic? By targeting the ecological impacts of climate change through the arctic food chain, the proposed “Emergency Antarctic Climate Treaty Protocol” views the changing arctic ecosystem as mirroring effects of climate change on human communities, where the reduction of the arctic zooplankton species speaks to failures of the current Antarctic Treaty to address CO2 emissions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".