New York State School of Industrial and Labor Relations

The assessment of apple quality is pivotal in agricultural production management, and apple ripeness is a key determinant of apple quality. This paper proposes an approach for assessing apple ripeness from both structured and unstructured observation data, i.e., text and images. For structured text data, support vector regression (SVR) models optimized using the Whale Optimization Algorithm (WOA), Grey Wolf Optimizer (GWO), and Sparrow Search Algorithm (SSA) were utilized to predict apple ripeness, with the WOA-optimized SVR demonstrating exceptional generalization capabilities. For unstructured image data, an Enhanced-YOLOv8+, a modified YOLOv8 architecture integrating Detect Efficient Head (DEH) and Efficient Channel Attention (ECA) mechanism, was employed for precise apple localization and ripeness identification. The synergistic application of these methods resulted in a significant improvement in prediction accuracy. These approaches provide a robust framework for apple quality assessment and deepen the understanding of the relationship between apple maturity and observed indicators, facilitating more informed decision-making in postharvest management.

In the aftermath of the 2018 migrant caravans, the Mexican government arrested two migrants’ rights activists, ¹ but not because they gave food or donated clothes to the caravaneros . The transgressive nature of their activism consisted of walking and organizing alongside people whose presence in the country was unauthorized. They were charged with smuggling-related crimes; but they were really “guilty” of solidarity. In this essay, we outline what solidarity entails, what compels various actors to join in, and to what end. From an interdisciplinary perspective, we discuss the “what,” “where,” “who,” and “why” of solidarity. The purpose is to open a new epistemological horizon, providing tools to collectively reflect on the complex issues at the intersection between solidarity, migration, and law.

This study examines the impact of mothers’ labor force participation (MLFP) on child time allocation to explore the associating factors with boys’ disengagement from education in developing regions. Using original time-use data from the rural Philippines and employing exogenous institutional changes in the regional labor market, the study finds that MLFP widens the gender gap in child time-allocation patterns, with daughters dedicating more time to educational activities than sons. This effect is particularly pronounced when formal working and self-employed mothers are compared, suggesting that daughters respond to their parents as role models in terms of occupational stability, which requires educational attainment. For boys, the study explores the mechanism behind the effect by comparing the extended family setting with other scenarios to determine whether diminished maternal opportunities to monitor children affect sons’ educational engagement. Overall, these findings contribute to an understanding of the complex dynamics between maternal employment and gender gaps in children’s human capital formation in conditions of poverty.

This article examines the trends in women’s economic outcomes in the United States, focusing primarily on labor force participation, occupational attainment, and the gender wage gap. Considerable progress was made on all dimensions prior to the 1990s followed by a slowing or stalling of gains thereafter, with a plateauing of female labor force participation trends and a slowing of women’s occupational and wage convergence with men. The author considers the likelihood that progress in narrowing gender gaps will resume in these areas, and concludes it is unlikely without policy intervention. She then considers new policy initiatives to address work–family issues and labor market discrimination that may help to increase female labor force participation and narrow gender inequities in the labor market.

With corporate litigation has gradually become one of the remarkable corporate risks and development constraints for Chinese firms, there is an increasing need for an empirical study that examine the impact of corporate litigation on CEO accountability. To address this need, this study uses bivariate logit estimations for panel data of 3746 Chinese publicly listed firms during 2009–2020 to demonstrate that corporate litigation is significantly associated with increased CEO turnover and compensation reduction. It further investigates the baseline effects across firm performance, pay disparity and ownership structure which present stronger effects for poor performers and private-owned firms, yet high pay disparity correlates with a greater likelihood of compensation reduction whereas low pay disparity is associated with a higher likelihood of CEO turnover. Moreover, while securities lawsuits increase CEO turnover probability, non-securities lawsuits could lead to either CEO turnover or CEO pay cut. This study is the first to investigate the impact of corporate litigation on CEO accountability in China. The evidence supports the idea that top executives should be held accountable when firms encounter corporate litigation.

This paper intends to solve the limitations of the existing methods to deal with the comments of tourist attractions. With the technical support of Artificial Intelligence (AI), an online comment method of tourist attractions based on text mining model and attention mechanism is proposed. In the process of text mining, the attention mechanism is used to calculate the contribution of each topic to text representation on the topic layer of Latent Dirichlet Allocation (LDA). The Bidirectional Recurrent Neural Network (BiGRU) can effectively capture the temporal relationship and semantic dependence in the text through its powerful sequence modeling ability, thus achieving a more accurate classification of emotional tendencies. In order to verify the performance of the proposed ATT-LDA- Bigelow model, online comments about tourist attractions are collected from Ctrip.com, and users’ emotional tendencies towards different scenic spots are analyzed. The results show that this model has the best emotion classification effect in online comments of scenic spots, with the accuracy and F1 value reaching 93.85% and 93.68% respectively, which is superior to other emotion classification models. The proposed method not only improves the accuracy of sentiment analysis, but also provides strong support for the optimization of tourism recommendation system and provides more comprehensive, objective and accurate tourism information for scenic spot managers and tourism enterprises. This achievement is expected to bring new enlightenment and breakthrough to the research and practice in related fields.

This article investigates worker voice as a dimension of job quality and examines its link with job‐related outcomes. We refine and test a multi‐measure concept of the ‘voice gap’ to capture how much influence workers expect to have compared to what they actually have on a set of work‐related issues. Analysing a survey of 1307 American workers, we find that workers distinguish between a voice gap on issues related to their own interests (‘worker‐issues voice gap’) and those related to their employing organization's interests (‘organizational‐strategy voice gap’). Even after controlling for other dimensions of job quality, a larger voice gap is statistically associated with lower job satisfaction and well‐being, as well as higher levels of burnout and turnover intention. Additionally, we find that worker‐issues voice gap has a stronger and more significant effect than an organizational‐strategy voice gap. Based on these results, we recommend incorporating the voice gap measure in future worker voice research and as a practical tool for evaluating voice as a dimension of job quality.

Fake news in large-scale social networks is relatively rare, resulting in poor detection performance of deep learning method without sufficient samples. Meantime, false information comes from various sources and forms in large-scale social networks, which increases the difficulty of detection by simple Bayesian decision. Therefore, a method for detecting fake news in large-scale social networks based on a generalized Bayesian classifier is proposed. By using web crawlers to collect news in social network from multiple platforms such as entertainment, education, and medical diseases, and employing the HITS (Hyperlink-Induced Topic Search) algorithm to analyze webpage links, the accuracy of webpage target data retrieval is improved. A network data cleaning function is utilized to remove redundant and cluttered data from social network. A multi-modal Transformer model is employed to extract fusion features of text and image from large-scale social network data. By optimizing the Bayesian classifier using a greedy selection algorithm, a generalized Bayesian classifier is obtained. The extracted features of fake news from social networks are used as inputs to the generalized Bayesian classifier to obtain the prior probability of fake news in social networks. Based on this prior probability, evidence factors that meet the conditions of fake news in large-scale social networks are obtained. By evaluating the numerical values of these evidence factors, the classification and detection of fake news in large-scale social networks are achieved. Experimental results show that the maximum KL divergence value of the proposed method is 0.01, and the maximum Gini coefficient value is 0.1, indicating excellent performance in information cleaning and feature extraction. The maximum number of false positive results is only one sample, demonstrating its ability to accurately detect Fake News in social networks.

Background Ewing sarcoma (ES) of the ethmoid sinus with orbital involvement in an adult is very rare, with 16 reported cases in the literature. Immunohistochemical studies show small blue round cells positive for CD99 and fluorescence in situ hybridization (FISH) testing reveals positivity for the EWSR1 gene. Methods A 38‐year‐old male with a diagnosis of ES of the ethmoid sinus presented with left‐sided periorbital pain and edema, rhinorrhea, and proptosis. The patient underwent neoadjuvant chemotherapy, surgical resection of the left skull base, and postoperative proton radiotherapy. Results The patient tolerated chemotherapy, surgical resection, and adjuvant proton radiotherapy well with resolution of proptosis, diplopia, and pain. Due to local recurrence, he is currently undergoing adjuvant chemotherapy. Conclusion Our findings provide insight on the clinical presentation and appropriate management of extraosseous ES, specifically in the ethmoid sinus in the adult population.

In the knowledge‐based economy, creative ideas are becoming increasingly valuable. However, creators often encounter the threat of idea theft, which can discourage them from sharing their ideas and receiving vital feedback. This article explores the psychology behind creators' attempts to strategically manage idea sharing. Across three studies, we find that creators mispredict the preferences of idea thieves, such that idea thieves prefer to steal ideas in earlier stages of development than creators expect. We find this difference is driven by creators' tendency to underestimate how much idea thieves attend to moral concerns while deciding when to steal an idea. Further, we show that these mispredictions are consequential because they influence the stage at which creators choose to share their ideas for feedback.

Book Review of 'Unionizing the Ivory Tower: Cornell workers’ fifteen-year fight for justice and a living wage', by Al Davidoff (2023). Ithaca and London: ILR Press. 238 pages, ISBN: 9781501771552

In the expanding field of the gig economy, the interactions between app-workers and customers have become focal areas of academic investigation. Drawing from the conservation of resources (COR) theory, we propose and test a moderated dual mediation model to examine the impact of customer injustice on app-workers’ work outcomes, including withdrawal behaviors and service performance. Employing a mixed-method approach comprising two multi-wave, multisource field studies and an online scenario experiment, our findings provide support for the following hypotheses: customer injustice fosters withdrawal behaviors and undermines service performance by inducing app-workers to experience increased emotional exhaustion and reduced service-oriented self-efficacy. Nevertheless, the impacts of these associations are weakened when app-workers engage more frequently in online community support seeking behaviors. Theoretical implications and practical applications of our findings are discussed in the context of the burgeoning gig economy.

The small hive beetle Aethina tumida (SHB) Murray,1867, is an invasive bee pest that is expanding its range across Latin America, parts of Australia and the Philippines, and is now established in two regions in Italy. However, despite multiple recent introductions, there is scant information about the dynamics of the initial stages of colonization of the SHB and this knowledge gap could impact management and quarantine strategies decisions for many countries. This note describes the monitoring strategies and the patterns of SHB establishment in a previously SHB‐free apiary on the island of Oahu, Hawaii in 2010–2011. The weekly hive inspections, conducted over a ten‐month period, showed that beetle prevalence increased slowly at the apiary level, and adult beetles were more commonly found (87.9%) inside the oil traps that were placed inside the hives between the outermost frames of the hive. There were relatively few “free roaming” beetles detected at this point and they were more often found on the side frames and underneath the cover of the hive, not on the floor of the hive. The results also suggest that in the early stages of colonization careful visual inspections of the frames of each colony had relatively low detection success when compared to oil traps. Our results support previous modelling studies that suggest the need to inspect a high proportion of colonies per apiary (>80%) to ensure a 5% detection rate during the initial stages of invasion.

Objective The study determined the effects of corporate wellness programs (CWP) on Filipino workers’ physical, occupational, socio-emotional, intellectual, and spiritual wellness. Methods The study looked into the components of a CWP, its forms of communication, the respondents’ level of participation, motivation, and their physical, occupational, socio-emotional, intellectual, and spiritual well-being to determine their wellness status during the pandemic. The study utilized an online survey to examine questions related to the efficacy of such programs, descriptive statistics, correlation analysis to assess the respondents’ socio-demographic profiles, and point biserial correlation to test the association of CWP to their wellness status. Results The research showed that 90% of the respondents participated in their organization’s CWP, contradicting most studies that state CWP suffers from a low participation rate. CWP initiatives are mostly publicized through electronic mail, printed in memos, then posted on the bulletin board, and shared through the company website and social media. In addition, the study showed that overall wellness mean scores were higher in employees who were aware of their wellness programs than those who were not and in participating vis-à-vis non-participating employees. Conclusion The study’s six assumptions showed positive results, indicating that CWPs are beneficial in improving employees’ overall wellness. However, the per paradigm and overall wellness scores were weakly associated with participation and awareness status based on the point biserial correlation. No adverse effects were recorded in the study. In addition, the study discovered that employees were active in personal wellness initiatives, leading to high scores in their wellness dimensions. The study showed different individual wellness initiatives implying that employees were also proactive about their total well-being.

In the realm of innovation, relying solely on the creativity of researchers may not fully unleash their potential. Previous studies revealed the positive impact of academic justice climate on researchers’ behavior, the impact of individual characteristics and work state on the effect has been underexplored. Based on the theory of the job demands resource, this study proposed the connotation of academic justice climate, spiritual creativity and spiritual depletion, and explore the impact of academic justice climate on innovation performance was investigated from two paths: spiritual creativity and spiritual depletion. Which involved the mediating role of work involvement and job burnout, along with the moderating roles of sensitivity and perceived organizational support. Data were collected from 289 researchers in universities and research institutions in China. Statistical analysis was conducted using regression analysis. On the one hand, the result shows respectively the definition about three terms, Academic justice climate refers to work resource availability including resource acquisition and resource created by research leaders from their own subjective preferences and profit-orientation. Spiritual creativity refers to individual under certain security environment can fully stimulate their personal potential to produce creation. Spiritual depletion refers to individual under certain insecurity or threatened environment, would be stuck in a painful situation, or negative mood and unable to move on. On the other hand, the results of analysis statistically support the hypothesized indirect relationship between the academic justice climate and researchers’ innovation performance. Work involvement and job burnout play a completely mediating role in the above relationships. Sensitivity positively regulates the impact of the academic justice climate on work involvement. Perceived organizational support positively regulates the impact of academic justice climate on job burnout. This research results show how and when academic justice climate can enhance researchers’ innovation performance, these findings not only contribute to enrich job demand resource theory, but also provide research organizations and researchers valuable reference about spiritual health management.

Automation’s extensive impact on the labor market and economy is well recognized, but the underlying motivations for its adoption remain understudied. To address this gap, we analyze an original dataset covering 1276 cities across 148 countries, using event history analysis to examine the adoption of automated metro systems. Our research suggests that city governments are driven by status competition in their decisions to automate subway systems. We find that high-status cities are more likely to adopt automation. However, this trend diminishes when cities are preparing to host a mega-event such as the Olympics, indicating that lower-status cities use these events as opportunities to adopt automation technologies. Our finding reveals that status-driven aspirations, manifesting in the spectacle of automation, are a significant motivator for adopting automated technologies, prompting further investigation into the socio-economic factors influencing automation and the symbolic importance of technological advancement across various economic sectors.