Imagining igorots : performing ethnic and gender identities on the Philippine Cordillera Central
Bibliographic record
Abstract
Gender, ethnicity, landscape, nation — none exist as real places or categories but as the effect of various practices that bring bodies and spaces into being. This dissertation attempts to rethink concepts of gender and ethnicity away from traditional ideas of places and cultures. To do so, it embeds them within social practice as performatives emerging from the colonial encounter. The text reports on ethnographic field research among Igorot communities originating on the Philippine Cordillera Central. By applying Burawoy's extended case method to local narratives of identity, history and migration, the argument extends theorizations of locality and gendered subaltern agency. The analysis locates the imaginative work that produces local places, subject positions and subjectivities within a palimpsest of transnational discourses, outmigration and local innovations. Locality and subjectivity are shown to be embedded in and produced by both local experiences and global identifications of difference originating within colonial histories. In narrating and dis-placing colonial stories of places and people, the power of these discourses on gender and ethnicity to constitute subjects with coherent names is challenged. By tracing the-persistence of the colonial past in the apparently de-colonized present, this text suggests that the concepts of performance and naming can help to make greater theoretical and empirical sense of the (post)colonial world.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".