Analyzing the Social and Cultural Determinants of Keeping and Using Firearms in Khuzestan Province
Notice bibliographique
Résumé
Introduction In many countries, including America, Canada, South Africa, Brazil, Colombia, and certain European nations, firearm-related injuries are a significant contributor to the overall number of deaths (Dahlberg, 2004). The majority of these incidents occur in countries where civilian firearm possession is unrestricted (Singh, 2005). According to a report from the United Nations, South Africa has the second highest rate of firearm-related deaths globally (Sanaei, 2004). In contrast, Iran has relatively few reported firearm injuries with the most recent official statistics from 2014 indicating over one million illegal firearms and a similar number of authorized firearms in circulation. Materials & Methods This study employed an interpretive approach to explore and elucidate participants' experiences and interpretations of firearm use by using qualitative methods. Specifically, the foundational data theory method was utilized among various qualitative research methods to conduct and present the research. Criterion sampling was employed to select all cases that met specific researcher-defined criteria. The participants included senior experts from the police deputy of the governorate, social deputy of the governorate, senior experts of the governorate, individuals arrested in this field, senior experts of the police force, academic experts, and citizens of Khuzestan Province (Ahvaz, Abadan, Izeh, and Shadgan cities). In-depth interviews were the primary technique used for data collection. Data analysis followed the systematic approach of contextual theory, employing open, axial, and selective coding methods. Common validation techniques were utilized to ensure the scientific rigor and trustworthiness of the research. Discussion of Results & Conclusion The data analysis revealed various factors within the research model. Causal conditions encompassed the quality and lack of official supervision, civil disobedience, symbolic function of weapons, feelings of deprivation and discrimination, demonstrative use of weapons, tribal power dynamics, strategic planning weaknesses, and anomic conditions. Additionally, tribal prejudice, identity reevaluation, identity-driven use of weapons, and background conditions (economic determinants), such as poverty, unemployment, perceived economic pressure, economic-social base of users, easy access to weapons, and generation of income through unauthorized weapon sales were identified. The intervening conditions (cultural determinants) included the influence of nomadic culture, patriarchal cultural stagnation, weapons as symbols of nobility and leadership honor, low cultural capital of users, delayed ethnic customs and traditions, lack of family socialization, inactive cultural organizations, lack of free time, ethnic reference groups, belief in honoring local traditions, and value of using weapons. The proposed strategies involved the necessity of enacting laws, regulating licensed weapons, continuous monitoring of weapon licenses, citizen-centered monitoring, developing cultural strategies to replace weapons, enhancing the efficiency of laws in local conflict resolution, and utilizing local trustees' capacity. The participants highlighted the significant consequences, including heightened insecurity, negative evaluation of local governance performance by citizens, and reduced sense of belonging, all revolving around the core category of "unbalanced reproduction of ethnic traditions."
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».