Local (or Not) Insecurity on Arctic Twitter/X: Global Insecurity and Climate Change
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An advance online version of this article was first published September 2024.While Twitter, now known as X, has been used to study political sentiments around elections and political discourse broadly speaking, less research has explored questions of insecurity. Using a data set of Arctic tweets between 1 January 2020 and 31 March 2023, and the R programming language, I asked how posts regarding this region framed the debate around insecurity. My work finds that spikes of insecurity on Arctic Twitter/X did not directly correlate with moments of global insecurity such as the Russian invasion of Ukraine in 2022 or the COVID-19 pandemic from early 2020. Instead, they reference environmental insecurities such as the 2020 Norilsk oil spill in Russia and other Arctic-specific events that almost all have to do with climate change, both locally and globally. These findings suggest that similar to public opinion polls, local insecurities have more resonance with Arctic publics, rather than highly politicized moments of global insecurity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it