Thirdworld-ist participatory action research (par), development dispossession (DD) and learning in indigenous and peasant struggles in Indonesia
Bibliographic record
Abstract
This paper addresses Thirdworld-ist PAR and its contributions towards organizing, networking and learning in social action in small peasant and indigenous anti-dispossession struggles addressing agro-extractive related DD in Baras, West Sulawesi, Indonesia. We elucidate the nature and role of Thirdworld-ist PAR praxis by mapping the following dimensions of learning in struggle against state-market led colonial capitalist dispossession: (a) learning to identify the agents of dispossession, the processes which enable dispossession and the related socioeconomic impacts of dispossession; and (b) learning in, from and for social action taken to address dispossession. We conclude by taking stock of the current situation and the continued role for Thirdworld-ist PAR in this context of dispossession. RINGKASAN (Bahasa, Indonesian) Artikel ini membahas PAR Dunia Ketiga dan kontribusinya terhadap pengorganisasian, jejaring, dan pembelajaran dalam aksi sosial perjuangan petani kecil dan masyarakat adat melawan development dispossession (DD/perampasan dalam pembangunan) oleh industri agroekstraktif di Baras, Sulawesi Barat, Indonesia. Kami membahas sifat dan peran praksis PAR Dunia Ketiga dengan memetakan dimensi pembelajaran berikut dalam perjuangan melawan perampasan kapitalis kolonial yang dijalankan pasar dan negara: (a) pembelajaran dalam mengidentifikasi agen perampasan, proses yang memungkinkan perampasan dan dampak sosialekonomi dari perampasan; dan (b) pembelajaran dalam, dari dan untuk aksi sosial mengatasi perampasan. Kami menutup tulisan ini dengan memaparkan situasi saat ini dan peran berkelanjutan PAR Dunia Ketiga dalam konteks perampasan ini.
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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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".