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Record W4225415025 · doi:10.20377/cgn-114

Legitimacy and Legitimation Practices: An Analysis of TSMO Networks

2022· article· en· W4225415025 on OpenAlex
Takumi Shibaike

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComplexity Governance & Networks · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPolitical Influence and Corporate Strategies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLegitimationLegitimacyHegemonyHierarchyPoliticsIncentiveDisciplinePopulationPolitical scienceSociologyPublic relationsPolitical economySocial scienceLawEconomics

Abstract

fetched live from OpenAlex

Private transnational organizations have grown in number and in influence. However, sociologists and political scientists often study them separately, either as transnational social movement organizations (TSMOs) or the larger category of international non-governmental organizations (INGOs). In this paper, I examine the determinants of TSMO legitimacy by drawing on the literature on INGOs. In so doing, I call for bridging the disciplinary gap between sociology and political science. Empirically, I find that legitimation benefits already prominent organizations more than those that are not. Networking thus helps reproduce the hierarchy among the TSMOs, challenging the earlier notion that TSMOs are horizontally networked. However, I also find that Southern TSMOs are more likely to gain legitimacy than Northern TSMOs once they are visible to their peers. The analysis of TSMOs thus cautions our bias to study Northern INGOs and generalize the findings to INGO population. Overall, my findings reveal that the incentives and strategies that INGO research has documented exist among TSMOs despite their counter-hegemonic ambitions.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.511
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.073
GPT teacher head0.290
Teacher spread0.217 · 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