Clandestine Organizations, al Qaeda, and the Paradox of (In)Visibility: A Response to Stohl and Stohl
Bibliographic record
Abstract
In a recent article published in this journal, Stohl and Stohl (2011) examine the phenomenon of clandestine organizations from a communication-centered perspective. The authors draw primarily on the work of the ‘Montreal School’ of organizational communication, which stresses the constitutive role of communication for organizations. In this response, we argue that the Stohls’ paper does not make full use of the paradigmatic turn that the Montreal School offers to organization studies. In our view, the authors overemphasize the role of communication among organizational members in the constitution of organizations. In contrast, we argue that organizations can also be ‘talked into existence’ by the communicative acts of third parties (e.g., the media), a view that is consistent with the Montreal School’s work. Moreover, drawing on the Stohls’ central example of the terrorist organization al Qaeda, we suggest that the attribute ‘clandestine’ does not capture the essence of that organization because it is characterized by extreme invisibility of its governance structures and by extreme visibility of its terrorist activities. We believe it is the reversion of the relation between invisibility and visibility that differentiates al Qaeda from legitimate organizations such as private businesses and ensures its perpetuation against all odds.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.047 |
| Scholarly communication | 0.010 | 0.023 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.014 | 0.013 |
| 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".