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Enregistrement W2943299412 · doi:10.32580/idcr.2019.11.1.1

Does Gender Mean Women in International Development? Focusing on the Bureaucratization of the Gender Discourse

2019· article· en· W2943299412 sur OpenAlexaboutno aff
Eun Kyung Kim

Notice bibliographique

RevueKorea Association of International Development and Cooperation · 2019
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueGender Politics and Representation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGender mainstreamingMillennium Development GoalsSustainable developmentGender equalityPolitical scienceInternational developmentGender studiesTransformative learningMainstreamingSociologyPovertyLaw

Résumé

récupéré en direct d'OpenAlex

연구목적: 이 글은 다양한 페미니스트 학자들의 선행연구에 기반 하여 국제개발 규범에서 젠더의 개념이 확산되어 성주류화라는 개념으로까지 발전되어 온 상황에서, 젠더와 여성이라는 용어가 명확한 구분 없이 함께 쓰이고 있는데 대한 문제의식에서 출발하였다. 이 글은 국제개발 규범에서 ‘젠더’가 ‘여성’과 등치되는 현상에 대해 의문을 제기하고, 성평등 달성을 위한 성주류화 전략 속에 젠더 개념이 얼마나 적용되었고 실천되고 있는지 분석하고자 하였다. 연구의 중요성: 국제개발 규범과 현장에서 젠더와 개발 담론이 어떻게 적용되고 있는지에 대해 SDGs 지표와 CIDA 등 국제개발 현장의 현실을 통해 분석함으로서 젠더와 여성이라는 언어가 어떻게 정치적으로 혹은 실용적으로 사용되고 있는지 보여주고 있다. 연구방법론: 국제개발 규범으로 대표적인 MDGs와 SDGs의 성평등 목표와 관련 지표에 대해 젠더관점에서 분석하고, 국제개발 현장의 사례를 보여주기 위해 캐나다와 한국의 사례를 분석하였다. 연구결과: 국제개발 규범과 양자기구 문헌을 분석한 결과 성주류화가 확산되는 과정에서 젠더의 개념이 기술관료제화 되었고, SDGs 젠더통합적 목표의 지표들은 젠더의 개념보다는 여성이라는 접근으로 구성되어 있다는 점, 한국을 비롯한 해외 국제개발의 현장에서도 젠더라는 용어는 정치적 저항이나 일반인과 소통의 어려움 등의 이유로 여성이라는 언어로 사용되고 있다는 점을 확인하였다. 결론 및 시사점: 국제개발에 있어서 젠더는 기술관료제화 된 여성이라는 언어로 대체되고 있는데, 이는 단기간에 성과를 측정해야하는 정부의 압박과 궁극적으로는 젠더 관계 변화에 대한 저항 등의 원인이 있었다는 점을 상기해야 한다. SDGs가 내걸고 있는 젠더 통합적 목표들이 전환적인(transformative) 변화를 가져올 수 있기 위해서는 젠더 개념을 기술관료적 개념이 아닌 젠더권력 구조 안에서 이해하고 실천에 옮길 때 가능해질 것이다.Purpose: This paper aims to review how discourses on gender have evolved in the midst of transformation from MDGs to SDGs and how gender has been reflected in international development norms. Moving from MDGs to SDGs, feminists have raised their voice to point out gender issues that are missing in MDGs and have demanded that SDGs include fundamental agenda required to achieve gender equality. In international development, gender discourses have developed from WID to GAD from the 1970s through to the mid-1990s. How deeply these discourses are reflected in and embraced by MDGs and SDGs is the main question, because it has been witnessed that the terminology has gone back to “women” instead of “gender.” Originality: It shows how the language of gender and women is being used politically or practically. Methodology: In the international development norms, gender equality goals and related indicators of representative MDGs and SDGs were analyzed from the gender perspective, and case studies of Canada and Korea were analyzed to show cases of international development. Result: The first part of the paper illustrates how gender discourses have evolved in the field of development cooperation, focusing on WID, GAD, and gender mainstreaming. In the second part, the paper highlights the difference between the norms and the actual practice of gender mainstreaming strategies. Next, it analyzes how WID and GAD discourses have been embedded in MDGs and SDGs, along with their limitations. The last section looks into the meaning of “gender mainstreaming” and women and girls’ empowerment in the actual practice of development projects and gender mainstreaming strategic tasks that are required to achieve gender equality goals within the frame of SDGs. Conclusion and Implication: Finally, it attempts to draw attention to two points. The first is the concept that gender in development cooperation has been de-politicized to name a biological woman in contrast to the one that the feminists used. The second point is how the gender-integrated goals of the SDGs can bring about a transformative change; this is possible when the gender concept is understood and practiced in a gendered power structure rather than in a technical bureaucratic concept.

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)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,196
Score d'incertitude au seuil0,238

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
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 Opus0,020
Tête enseignante GPT0,285
Écart entre enseignants0,265 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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

Citations2
Publié2019
Routes d'admission1
Résumé présentoui

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