The Faces of Bureaucracy: A multi-method study of civil servant stereotypes and their consequences
Notice bibliographique
Résumé
Prejudices about civil servants have been prevalent for centuries, with civil servants often the subject of negative stereotypes and jokes. In her dissertation The Faces of Bureaucracy, Isa Bertram explores these stereotypes and their impact on public service through four empirical studies. The first study offers an international comparison, surveying citizens in the Netherlands, Canada, South Korea, and the United States. The findings revealed that stereotypes about civil servants vary by region. In North America, stereotypes were mostly positive, with civil servants viewed as hardworking, helpful, and responsible. In contrast, in the Netherlands and South Korea, stereotypes were more negative, with civil servants seen as inflexible, boring (Netherlands), or even corrupt (South Korea). Bertram’s second study examines whether stereotypes differ across socioeconomic status. She found that people with lower income levels generally held more negative views of civil servants than those with higher income levels. However, the differences were more about the types of traits associated with civil servants. Lower-income individuals were more likely to view civil servants as strict and arrogant, while higher-income individuals focused more on work-related traits, such as leaving work early. The third study investigates how stereotypes affect citizens’ experiences with public services. Results of this survey experiment indicated a confirmation bias effect of the stereotypes, where citizens’ expectations based on stereotypes shaped their experiences. Participants with negative stereotypes activated tended to report lower satisfaction and poor experiences with public services, while those with positive stereotypes activated had more favorable experiences. These findings contrast with the expectation-disconfirmation model, which is commonly used to assess satisfaction with public services. In her final study, Bertram interviewed civil servants to understand how they perceive these stereotypes and cope with them. Respondents generally didn’t view stereotypes as a problem for their personal wellbeing – they were concerned about the impact on public service and the relationship between citizens and the government, for instance regarding trust. In addition, respondents used different perspectives to make sense of the stereotypes: Some saw them as based in truth, while others viewed them as an inevitable consequence of the complex nature of government work. These differing perspectives helped civil servants cope with the negativity, offering a form of self-protection – however, this form of coping can also lead to blind spots, for instance in interpreting critical citizen feedback. Taken together, Bertram’s research illustrates that civil servant stereotypes are multifaceted and closely intertwined with other related concepts, such as trust in government and perceptions of public organizations. In addition, the research underscores the importance of considering the contextual reality of public administration and public services when studying the consequences of civil servant stereotypes. In sum, the research highlights that in studying civil servant stereotypes, we can benefit from a nuanced approach to understanding what they are and what they represent: In part, overgeneralized misconceptions, but also reflections of misunderstandings between citizens and the public sector, justified criticisms of public services, or even truths about bureaucratic tendencies.
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Prédiction distillée sur la base complète
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Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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