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Article
Publication date: 11 October 2022

Carly Dearborn and Michael Flierl

This paper begins to construct a theoretical foundation for using a diplomatic-informed pedagogy that specifically addresses common concerns in archival instruction in a higher…

Abstract

Purpose

This paper begins to construct a theoretical foundation for using a diplomatic-informed pedagogy that specifically addresses common concerns in archival instruction in a higher education environment. The authors utilize self-determination theory (SDT) to define student-centeredness and provide empirical guidance for creating a learning environment supporting student motivation, persistence and academic achievement. The proposed framework provides both structure and theoretical grounding for the archivist while also cultivating a learning environment which effectively motivates novice researchers.

Design/methodology/approach

The authors draw on diplomatics and archival instructional literature to propose an instructional framework utilizing SDT.

Findings

A diplomatic-informed pedagogy is a new, theoretically viable approach to archival instruction for novice researchers intending to replace common archival orientation and competency-based instruction. This pedagogical approach also provides a reproducible structure to the instructional archivist, helping to organize classroom learning outcomes, assessments and activities in alignment with evidence-based research and well-established archival theory.

Research limitations/implications

This is a conceptual paper and based on subjective analysis of existing literature and theory. The proposed framework has not been tested in a practical application, but it is based in the pedagogical foundations of diplomatics and SDT's focus on student perceptions and motivations.

Originality/value

Diplomatics, the foundation of archival science and legal theory, can be applied pedagogically to provide concrete guidance to teach students to use archives in more intentional, creative and disciplinary authentic ways. Diplomatics gives the instructional archivist a pedagogical foundation, structure and guiding methodology to approaching novice researchers in the archives, while SDT presents how to implement such an approach.

Article
Publication date: 25 December 2023

María Angela Prialé, Jorge E. Dávalos, Brian Daza and E. Frances Ninahuanca

The purpose of this paper is to identify the causal (not correlational) effect of women’s entrepreneurship on corporate social responsibility (CSR) practices in Latin America.

Abstract

Purpose

The purpose of this paper is to identify the causal (not correlational) effect of women’s entrepreneurship on corporate social responsibility (CSR) practices in Latin America.

Design/methodology/approach

This study builds on a hitherto unexploited sparse data set on Latin American B Corporations to identify the causal relationship of interest and on a (synthetic) instrumental variable method.

Findings

The results confirm that women’s entrepreneurship has a positive causal effect on social responsibility. This study finds that an increase of 1% in the proportion of women entrepreneurs leads to an increase of 0.5 in the B Impact Assessment score, the CSR indicator.

Originality/value

This study contributes to the literature by providing robust statistical evidence of a causal relationship between women entrepreneurs and social responsibility practices in the Latin American context. This research captures the multidimensional nature of social responsibility by using a comprehensive and vast metric of CSR obtained from the data of the B Impact Assessment tool. This study illustrates how machine learning methods can be used to address the lack of structure of the Latin American B Impact Assessment data.

Propósito

El propósito de esta investigación es identificar el efecto causal (no correlacional) del emprendimiento de mujeres en las prácticas de responsabilidad social empresarial (RSE) en América Latina.

Metodología

Nos basamos en un conjunto de datos escasamente explorado hasta el momento sobre las Empresas B en América Latina para identificar la relación causal de interés, y utilizamos un método de Variables Instrumentales (VI) sintéticas.

Hallazgos

Nuestros resultados verifican el efecto causal positivo del emprendimiento de las mujeres en la responsabilidad social. Descubrimos que un aumento del 1% en la proporción de mujeres emprendedoras conduce a un aumento de 0.5 en la puntuación de la Evaluación de Impacto B, nuestro indicador de RSE.

Originalidad

Contribuimos a la literatura proporcionando evidencia estadística sólida de una relación causal entre emprendedoras mujeres y prácticas de responsabilidad social en el contexto de América Latina. Esta investigación captura la naturaleza multidimensional de la responsabilidad social mediante el uso de una métrica amplia y vasta de RSE obtenida de los datos de la herramienta de Evaluación de Impacto B. Ilustramos cómo se pueden utilizar métodos de aprendizaje automático para abordar la falta de estructura de los datos de evaluación de impacto B en América Latina.

Objetivo

O propósito desta pesquisa é identificar o efeito causal (não correlacional) do empreendedorismo feminino nas práticas de responsabilidade social corporativa (RSC) na América Latina.

Metodologia

Baseamo-nos em um conjunto de dados escasso até então não explorado sobre as Empresas B na América Latina para identificar a relação causal de interesse, e utilizamos um método de Variáveis Instrumentais (VI) sintéticas.

Resultados

Nossos resultados verificam o efeito causal positivo do empreendedorismo feminino na responsabilidade social. Descobrimos que um aumento de 1% na proporção de mulheres empreendedoras leva a um aumento de 0,5 no escore de Avaliação de Impacto B, nosso indicador de RSC.

Originalidade

Contribuímos para a literatura fornecendo evidências estatísticas robustas de uma relação causal entre empreendedoras mulheres e práticas de responsabilidade social na América Latina. Esta pesquisa captura a natureza multidimensional da responsabilidade social usando uma métrica abrangente e vasta de RSC obtida a partir dos dados da ferramenta de Avaliação de Impacto B. Ilustramos como métodos de aprendizado de máquina podem ser usados para lidar com a falta de estrutura dos dados de avaliação de impacto B na América Latina.

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