Bibliographic record
Abstract
Moving away from the conventional geopolitical analyses of territory, states, and nations, geographical research is now focused on the ways that political identities are constituted in and through spaces and places at various sites and scales. Many geographers attend to how power gets articulated, who gets marginalized, and what this means for social justice. Poststructuralist theory problematized the fundamental premise that the literal subject is resolutely individual, autonomous, transparent, and all knowing. Feminist and critical race scholars have also insisted that the self is socially embedded and intersubjective, but also that research needs to be embodied. There are four prominent and inherently political themes of analysis in contemporary geographical research that resonate with contemporary events: nation states and nationalism; mobility and global identities; citizenship and the public sphere; and war and security. Geographers have critically examined the production and reproduction of national identity, especially salient with the rise of authoritarianism. Geographers have also focused on the contemporary transnationalization of political identity as the mobility of people across borders becomes more intensive and extensive because of globalization. Consequently, globalization and global mobility have raised important questions around citizenship and belonging. Rethinking war and the political, as well as security, has also become a pressing task of geographers. Meanwhile, there has been a growing attention to the political identities of academics themselves that resonates with a concern about forms of knowledge production. This concern exists alongside a critique of the corporatization of the university. Questions are being raised about whether academics can use their status as scholars to push forward public debate and policy making.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".