Investigating Loss and Damage in Coastal Region of Bangladesh from Migration as Adaptation Perspective: A Qualitative Study from Khulna and Satkhira District
Notice bibliographique
Résumé
This study aims to examine the loss and damage experienced by coastal regions from the perspective of adaptation. It also seeks to evaluate the adaptation techniques employed when migration is utilized as a significant approach to mitigate the effects of loss and damage on coastal communities. This study evaluates the extent of loss and damage caused by constraints on adaptation. Two districts, Khulna and Satkhira, in the Khulna division of Bangladesh, were chosen for the study. In these districts, a total of twenty-four detailed interviews and one focus group discussion (FGD) were conducted with individuals living in rural areas whom climate-related effects and disasters have impacted. Additionally, seven interviews were conducted with climate migrants residing in informal settlements within the words of Khulna City Corporation. The process of identifying appropriate interview candidates involves utilizing a combination of specific criteria and snowball sampling techniques. The study employed NVivo 14 software to conduct theme analysis on textual data obtained from interviews. In the coding procedure, we sequentially employed semantic coding, latent coding, categorization, pattern exploration, and theme creation, all of which were in line with the research aim. The study indicates that most affected persons utilize seasonal and temporary movement as an adaptive strategy to deal with the slow effects of climate change, such as increasing temperatures and salinity in rural regions, and when they encounter limitations in their ability to adapt. Conversely, they opted for permanent migration in response to stringent constraints imposed by severe climate events like cyclones and river erosion, leaving them with no alternative but to move to urban regions. Social networks are crucial in influencing migration choices, as several families depend on information provided by urban relatives and rural neighbors to inform their relocation decisions. Nevertheless, not all individuals impacted by the situation express a desire to relocate; others opt to remain in rural areas due to their sentimental attachment to their birthplaces and a sense of dedication to their ancestral territory. Due to the exorbitant cost of urban life, they believe that opting not to migrate is a more practical option for addressing the repercussions of climate-induced loss and damage. The study’s findings aid policymakers in determining migration strategies and policies to address the adverse effects of coastal population displacement in Bangladesh. Additionally, it aids in determining strategies to address the challenges faced by climate migrants in both urban and rural environments.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,008 | 0,005 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».