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Record W7132884213

The Determinants and Dimensions of Armed Group Taxation

2025· dissertation· W7132884213 on OpenAlexfundno aff
Tanya Elizabeth Bandula-Irwin

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldSocial Sciences
TopicBangladesh Politics, Society, and Development
Canadian institutionsnot available
FundersInternational Development Research CentreUniversity of TorontoRoyal Bank of CanadaUnited States Agency for International Development
KeywordsCorporate governanceTransformative learningInstitutionState (computer science)Tax revenueArgument (complex analysis)Function (biology)RevenueIslam
DOInot available

Abstract

fetched live from OpenAlex

Why do some armed groups tax while others do not? When they do tax, how do they develop their taxation systems, and what determines whether taxation is enforced coercively or more contractually? This dissertation investigates the prevalence, institutionalization, and nature of armed group taxation (AGT) to understand its implications for governance, legitimacy, and conflict outcomes. While taxation has long been viewed as a defining function of the state, armed groups frequently engage in taxation as part of their broader governance practices, particularly in contexts where the state is fragile, contested, or absent. Taxation is the most common governance practice of armed groups, yet it remains underexplored as a distinct wartime institution despite its potentially transformative effects. This dissertation argues that AGT varies along three key dimensions: its prevalence, its degree of institutionalization, and the extent to which it is enforced coercively or contractually. The argument is structured around three interrelated questions: (1) When do armed groups tax? (2) When do they institutionalize taxation? and (3) When do they tax in more contractual ways? Drawing on a global quantitative analysis and a comparative case study of the Moro Islamic Liberation Front (MILF) and the Communist Party of the Philippines-New People’s Army (CPP-NPA), this research demonstrates that AGT is shaped by three primary factors: revenue imperatives, feasibility (military and organizational capacity), and community embeddedness. The findings show that while financial pressures drive armed groups to tax, their ability to do so is constrained by military strength and organizational capacity, which are necessary for enforcing compliance. When groups lack these capabilities, taxation remains infeasible, regardless of financial need. However, even among groups that successfully institutionalize taxation, the mere existence of tax systems does not automatically lead to more contractual or reciprocal relationships with taxpayers. Instead, community embeddedness and the conditional role of non-tax revenues shape the nature of taxation. Embedded groups with access to alternative revenue sources are more likely to allocate resources toward public goods and services, reinforcing taxation as a governance tool rather than mere extraction. In contrast, groups that lack embeddedness and face acute financial desperation—particularly those without non-tax revenues—are more likely to apply more coercive taxation to wealthier taxpayers, such as foreign businesses or political actors, while engaging minimally with the broader populations. As a result, taxation by non-embedded groups is more likely to be perceived as coercive, whereas embedded groups with financial stability are better positioned to cultivate reciprocal fiscal relationships with taxpayers, towards a more contractual approach to taxation. This dissertation makes three key contributions. First, it develops a framework for conceptualizing AGT as a distinct phenomenon, challenging the common conflation of taxation with extortion or looting. Second, it provides empirical evidence on the prevalence and institutionalization of armed group taxation, showing how taxation systems evolve over time in response to revenue pressures and feasibility. Finally, it examines the role of AGT in shaping wartime political orders, highlighting its potential to foster governance legitimacy or deepen coercion, with implications for state-building and post-conflict transitions. By treating taxation as a central component of rebel governance, this research advances our understanding of how armed groups interact with local populations and the conditions under which they develop state-like institutions.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.004
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.025
GPT teacher head0.366
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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