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Applying the WWII Sabotage Manual to the IS Discipline: Are We Self-Sabotaging?

2025· article· en· W6998709892 sur OpenAlexaff

Notice bibliographique

RevueJournal of the Association for Information Systems · 2025
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueInformation Systems Theories and Implementation
Établissements canadiensOntario Tech University
Organismes subventionnairesnon disponible
Mots-clésAgency (philosophy)Relevance (law)Action (physics)State (computer science)Information systemField (mathematics)World War II
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Since the birth of humanity, sabotage – the intentional action aimed at weakening a particular entity such as a state, an organization, a group of people, or an individual – has been present in virtually all areas of life. In the management context, this concept gained attention in the early 19th century during the infamous Luddite movement, when workers sabotaged machinery to protest against their employers who replaced manual labor with technology. Sabotage also plays a critical role in wartime, but such actions are generally shrouded in secrecy. Recently, the U.S. Central Intelligence Agency (CIA) declassified the Sabotage Field Manual developed by the Office of Strategic Services (the predecessor of the CIA) and used during World War Two to train prospective citizen-saboteurs in German-occupied Europe (Office of Strategic Services, 1944). In addition to instructions pertaining to direct physical sabotage – destroying and paralyzing critical equipment, resources, and industrial systems – the manual focuses on indirect sabotage performed by managers, supervisors, and other decision-makers to interfere with and impede critical production processes in organizations. We focus on the latter category of sabotage and compare the manual’s instructions with the key functioning principles within the information systems (IS) discipline. Information systems scholars have traditionally been concerned with the state and evolution of their discipline. For example, previous inquiries have examined the nature of the discipline’s publication venues, the practical relevance of academic research, and citation practices. We seek to productively contribute to that discourse by analyzing whether IS has successfully developed a robust scholarly system or has, perhaps inadvertently, engaged in forms of self-sabotage. To do so, we draw upon our observations and experience in academia as well as debates among IS scholars such as those in CAIS (Kautz, 2018). We discuss how several instructions in the Sabotage Manual relate to behaviors, academic activities, and debates in the IS discipline. For example, Instruction 1 recommends to: Insist on conducting all activities through formal channels and avoid shortcuts that might expedite decision-making. When it comes to IS research, this occurs when reviewers insist on impossible levels of generalizability, realism, and precise measurement control in quantitative research. Instruction 2 recommends to: Bring up irrelevant issues and ask endless questions. The debates among IS scholars on whether IS is a Science and the relevance of IS research are prime examples of this. Instruction 3 says to: Haggle over precise wording in every document. Our failure to agree on a common definition for “Information System” is an example here. Instruction 4 states: Express concern about jurisdictional issues and policy contradictions. IS scholars apply this instruction by questioning the origins of our discipline and whether it has a core theory. Instruction 5 is: Provide incomplete or misleading instructions during employee training. An example here is that faculty request that IS research should strive to influence other fields but then only reward IS core citations in T&P processes. These are just a few examples, and there are more relating to research, teaching, and service, which we have identified and will discuss in the presentation.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,008
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,945
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0080,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0020,000
Communication savante0,0010,002
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,336
Écart entre enseignants0,322 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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