Homo Itinerans: Towards a Global Ethnography of Afghanistan By Alessandro Monsutti
Bibliographic record
Abstract
Alessandro Monsutti’s ethnography introduces a cogent rethinking of Afghan mobility. Monsutti’s long-term engagement with Afghan communities, built on two decades of ethnographic research, allows him to offer a nuanced perspective on how Afghans navigate and resist global social, political, and economic systems through mobility. In Homo Itinerans: Towards a Global Ethnography of Afghanistan, Monsutti examines Afghan mobility through the lens of global inequalities, colonial legacies, and the challenges of the post-2002 reconstruction. This book is the outcome of a long-time multi-sited ethnography that Monsutti has conducted in Afghanistan, Pakistan, Iran, EU, the USA, and Australia. He contends that US counterinsurgency and reconstruction strategies often mimic British colonial practices, where external standards aim to regulate Afghan society (Monsutti 2020, Chapter 1). This colonial gaze, entangled with the war industry since the Cold War, positions reconstruction as pacification of Afghan society rather than genuine development (Ibid). Monsutti critiques international bodies like the UN for relying on Western-educated Afghan elites to drive societal transformation, while on-the-ground realities indicate a fragmented sovereignty dominated by international influence.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".