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This conceptual paper aims to explore biases in reading textbooks that have been used to teach generations of Americans, including children in urban communities. While these texts are no longer used, the images they present and the ideas embedded in these texts unfortunately contribute to who we are as a nation.

These texts were identified by Catherine Compton-Lilly as she trolled the historical archives of a major university.

In addition to an analysis of historic texts, more recent attempts to create culturally responsive texts often designed to serve children in urban communities are examined, and the learnings from these attempts are being explored.

This conceptual paper points to the need for systematic analyses of biases operating in textbooks that are currently used in schools.

This work reveals and explores one way in which historical bias has historically infected the early learning experiences of young children in the USA.

Ethnographers and other qualitative social scientists have long reflected on the ways researcher identity – who we are – shapes how we see and understand what and whom we encounter in our research, and how research participants see and understand us. In “Insider–outsider–inbetweener? Researcher positioning, participative methods, and cross-cultural educational research,” Milligan (2016) takes up questions regarding researcher positionality in qualitative research in the field of comparative and international education. In particular, Milligan argues for the use of participative techniques to gain insider perspectives and to lessen unequal power relations between researcher and the researched in cross-cultural research. In this chapter, we will engage Milligan’s discussion of participative research by analyzing the similarities and differences in studying participants with relative social privilege versus studying those from marginalized communities. Specifically, we will reflect on two ethnographic studies that explored the global educational aspirations of middle and upper middle-class Asian students. Furthermore, we attempt to complicate the discussion of “cross-cultural” research by arguing that in the neoliberal global context, researchers and the researched may move back and forth across national and cultural boundaries. The chapter concludes by raising questions regarding the unique challenges of conducting cross-cultural studies that flow across national boundaries.

The aim of this paper is to provide additional insights on the association between real earnings management (REM) and crash risk, particularly from the perspective of an emerging market economy. It also examines the moderation role that internal and external corporate governance may play in this area.

Relying on archival data from the RESSET and CSMAR databases over a timeframe from 2010 to 2018 of China listed company, the authors test the hypotheses by regressing common measures of crash risk on the treatment variable (REM) and crash risk control variables identified in the prior crash risk literature. The authors also introduce monitoring proxies (internal controls as an internal governance and institutional ownership as an external governance) and assess how effective internal and external governance moderate the relation between REM and stock price crash risk.

The results suggest firms with higher REM have a significantly greater stock price crash risk, and that this association is mitigated by external monitoring. That is, greater institutional ownership, particularly pressure insensitive owners, mitigates the impact of REM on stock price crash risk. However, internal control does not mitigate the association between REM and stock price crash risk.

Following the passage of the Sarbanes–Oxley (SOX) Act, prior research has documented an increase in the use of REM and a positive association between REM and cash risk. The authors demonstrate that they persist in one of the largest emerging markets where institutional regulations, market conditions and corporate behaviors are different from those in developed markets. Also, the assessment of the moderation effect of internal and external governance mechanisms could have meaningful implications for investors and regulators in Chinese and other emerging markets.

For the case of many content features, This paper aims to investigate which content features in video and text ads more contribute to accurately predicting the success of crowdfunding by comparing prediction models.

With 1,368 features extracted from 15,195 Kickstarter campaigns in the USA, the authors compare base models such as logistic regression (LR) with tree-based homogeneous ensembles such as eXtreme gradient boosting (XGBoost) and heterogeneous ensembles such as XGBoost + LR.

XGBoost shows higher prediction accuracy than LR (82% vs 69%), in contrast to the findings of a previous relevant study. Regarding important content features, humans (e.g. founders) are more important than visual objects (e.g. products). In both spoken and written language, words related to experience (e.g. eat) or perception (e.g. hear) are more important than cognitive (e.g. causation) words. In addition, a focus on the future is more important than a present or past time orientation. Speech aids (see and compare) to complement visual content are also effective and positive tone matters in speech.

This research makes theoretical contributions by finding more important visuals (human) and language features (experience, perception and future time). Also, in a multimodal context, complementary cues (e.g. speech aids) across different modalities help. Furthermore, the noncontent parts of speech such as positive “tone” or pace of speech are important.

Founders are encouraged to assess and revise the content of their video or text ads as well as their basic campaign features (e.g. goal, duration and reward) before they launch their campaigns. Next, overly complex ensembles may suffer from overfitting problems. In practice, model validation using unseen data is recommended.

Rather than reducing the number of content feature dimensions (Kaminski and Hopp, 2020), by enabling advanced prediction models to accommodate many contents features, prediction accuracy rises substantially.

The purpose of this paper is to present a literature review of humanitarian logistics (HL) that aims to identify trends and suggest some directions for future research.

This conceptual paper develops a research framework for literature review through qualitative and quantitative content analysis. First, previous literature reviews in HL are updated and detailed. Then, seven classification criteria are added to earlier ones in order to advance the literature analysis.

The conclusions identify some literature gaps and research opportunities. The main conclusions are the need for more studies into the disaster recovery phase and the need for closer relationships between academia and humanitarian organizations to increase the number of applied research.

The literature is limited to academic peer-reviewed journals because of their academic relevance, accessibility, and ease of searching.

Help potential researchers to set up a research agenda for future work.

Reinforce earlier calls to increase truly applied research and improve social impact of the field.

In total, 228 papers that were published in the HL area are reviewed, giving rise to the most extensive literature review in this area. New dimensions for literature review in HL are proposed, which give some new insights into potential research directions.