Towards planetary-intimate social media research
Bibliographic record
Abstract
Feminist perspectives provide important impetus for more socially just research on and with social media platforms through a feminist ethics of care. However, a specific geographical conceptualization of social media platforms is still lacking. We argue for a feminist-geographical understanding of social media platforms and research as intertwined across planetary-intimate scales. We contend that feminist social media research must take seriously the planetary-intimate connections of social media platforms if it wants to contribute to the transformation of these capitalist, exploitative, unsustainable, and unjust digital systems. At the heart of planetary-intimate social media research are questions of power and the more-than-human context realizing social media platforms. We assert that social media platforms should not be viewed as discrete and disembodied in research with and on them, but rather as situated, embodied systems entangled across planetary-intimate scales. • Develops the concept of planetary-intimate social media platforms. • Understands social media platforms as situated, embodied systems across planetary-intimate scales. • Argues for a planetary-intimate approach to social media research to encourage more socially just ways of researching social media platforms.
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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 | 0.020 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.007 | 0.043 |
| Scholarly communication | 0.019 | 0.057 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 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".