Identity Labels Research Articles

The event attachment formation process of mega-event volunteers

ABSTRACT Although volunteers are important participants at mega-events, the changing relationship between volunteers and mega-events from the perspective of attachment remains under-explored. Taking the Beijing 2022 Winter Olympics as a case study, this study conducted a coding analysis of data collected through in-depth interviews and online materials. The results showed that the volunteers developed a sense of closeness to the Winter Olympics through the atmosphere, Olympic heritage, and place attachment in the pre-event stage. In the mid-event stage, on the basis of the new norms and order in space and time, the volunteers developed a strong sense of connection to the Winter Olympics through their experiences and perceptions of the event. In the post-event stage, they developed a sense of identification with the Winter Olympics through their internalisation of event memories, identity labels, and new habits. The volunteers’ attitudes showed a dramatic evolutionary conditional–unconditional–unreserved pattern together with self-transformation due to the Olympics. This study sheds light on future volunteer management and event development.

I know you are but who Am I? Presentation and labelling in young queer communities

Recent research shows a sharp increase in the number of queer-identified young people in the United States, along with an expansion of terms people use to describe their queer identities. Using semi-structured interview data collected from 30 queer-identified non-male 18-23-year-olds, we examine how young people today use terminology, identity, and appearance to communicate their sexual and/or gender identity. We find that the two most salient factors in how participants describe their sexual and gender identities are presentation and labelling. We then propose a distinction between one’s autonym and exonym, where an autonym is the identity label one uses to describe oneself and an exonym is the identity label others use to describe a person.

Pseudo-label assisted contrastive learning model for unsupervised open-set domain adaptation in fault diagnosis

The operation of mechanical equipment is frequently characterized by complexity and variability, leading to signal domain shifts. This phenomenon underscores the significance of cross-domain fault diagnosis for maintaining the reliability and safety of mechanical systems. Due to the absence of labeled data in many operational contexts, there's a clear need for an unsupervised domain adaptation technique that does not rely on labeled information. Moreover, traditional domain adaptation methods presuppose identical label distributions across source and target domains. Nevertheless, real-world engineering scenarios often present novel fault categories out of distribution, thereby challenging the efficacy of established domain adaption methods. To address these challenges, we proposed a pseudo-label assisted contrastive learning model (PLA-CLM) for Unsupervised Open-set Domain Adaptation. Based on contrastive learning, the proposed model effectively minimizes the discrepancy between samples of identical pseudo-label across domains, while simultaneously integrating distance, density, and entropy to isolate out-of-distribution samples. After training, the model adaptively identifies known faults and detects OOD faults using thresholds calculated based on sample distribution. Experimental results on two datasets demonstrate that our method surpasses existing approaches, ensuring enhanced reliability of mechanical systems’ operation and maintenance.

Ultra-inert lanthanide chelates as mass tags for multiplexed bioanalysis

Coordination compounds of lanthanides are indispensable in biomedical applications as MRI contrast agents and radiotherapeutics. However, since the introduction of the chelator DOTA four decades ago, there has been only limited progress on improving their thermodynamic stability and kinetic inertness, which are essential for safe in vivo use. Here, we present ClickZip, an innovative synthetic strategy employing a coordination-templated formation of a 1,5-triazole bridge that improves kinetic inertness up to a million-fold relative to DOTA, expanding utility of lanthanide chelates beyond traditional uses. Acting as unique mass tags, the ClickZip chelates can be released from (biological) samples by acidic hydrolysis, chromatographically distinguished from interfering lanthanide species, and sensitively detected by mass spectrometry. Lanthanides enclosed in ClickZip chelates are chemically almost indistinguishable, providing a more versatile alternative to chemically identical isotopic labels for multiplexed analysis. The bioanalytical potential is demonstrated on tagged cell-penetrating peptides in vitro, and anti-obesity prolactin-releasing peptides in vivo.

A Cross-Attention-Based Class Alignment Network for Cross-Subject EEG Classification in a Heterogeneous Space.

Domain adaptation (DA) techniques have emerged as a pivotal strategy in addressing the challenges of cross-subject classification. However, traditional DA methods are inherently limited by the assumption of a homogeneous space, requiring that the source and target domains share identical feature dimensions and label sets, which is often impractical in real-world applications. Therefore, effectively addressing the challenge of EEG classification under heterogeneous spaces has emerged as a crucial research topic. We present a comprehensive framework that addresses the challenges of heterogeneous spaces by implementing a cross-domain class alignment strategy. We innovatively construct a cross-encoder to effectively capture the intricate dependencies between data across domains. We also introduce a tailored class discriminator accompanied by a corresponding loss function. By optimizing the loss function, we facilitate the aggregation of features with corresponding classes between the source and target domains, while ensuring that features from non-corresponding classes are dispersed. Extensive experiments were conducted on two publicly available EEG datasets. Compared to advanced methods that combine label alignment with transfer learning, our method demonstrated superior performance across five heterogeneous space scenarios. Notably, in four heterogeneous label space scenarios, our method outperformed the advanced methods by an average of 7.8%. Moreover, in complex scenarios involving both heterogeneous label spaces and heterogeneous feature spaces, our method outperformed the state-of-the-art methods by an average of 4.1%. This paper presents an efficient model for cross-subject EEG classification under heterogeneous spaces, which significantly addresses the challenges of EEG classification within heterogeneous spaces, thereby opening up new perspectives and avenues for research in related fields.

Weakly Supervised Contrastive Learning for Unsupervised Vehicle Reidentification.

Reidentification (Re-id) of vehicles in a multicamera system is an essential process for traffic control automation. Previously, there have been efforts to reidentify vehicles based on shots of images with identity (id) labels, where the model training relies on the quality and quantity of the labels. However, labeling vehicle ids is a labor-intensive procedure. Instead of relying on expensive labels, we propose to exploit camera and tracklet ids that are automatically obtainable during a Re-id dataset construction. In this article, we present weakly supervised contrastive learning (WSCL) and domain adaptation (DA) techniques using camera and tracklet ids for unsupervised vehicle Re-id. We define each camera id as a subdomain and tracklet id as a label of a vehicle within each subdomain, i.e., weak label in the Re-id scenario. Within each subdomain, contrastive learning using tracklet ids is applied to learn a representation of vehicles. Then, DA is performed to match vehicle ids across the subdomains. We demonstrate the effectiveness of our method for unsupervised vehicle Re-id using various benchmarks. Experimental results show that the proposed method outperforms the recent state-of-the-art unsupervised Re-id methods. The source code is publicly available on https://github.com/andreYoo/WSCL_VeReid.

Are masculine faces “natural” for all men?: an experimental study about predictors of Chinese young adults’ attitudes towards trans men

ABSTRACT Researchers have increasingly paid attention to prejudice against trans people and its predictors. However, few studies have explored if potential predictors may interact to affect people’s attitudes towards trans people. In this experimental study, we examined the impacts of participant-related factors (i.e. gender and prior contact experience with gender or sexual minorities), target-related variables (i.e. gender identity and facial appearance), and their interactions on Chinese young adults’ attitudes towards trans men. We recruited 172 Chinese young adults to rate images of men with different gender identity labels (i.e. cisgender or trans men) and facial appearances (i.e. feminine or masculine). Results showed that a three-way interaction existed among targets’ gender identity labels, targets’ facial appearances, and participants’ genders. Overall, female participants were less likely than men to show more negative attitudes towards trans men than cisgender men. Participants showed more positive attitudes towards masculine-appearing trans men than feminine trans men. The current findings implied that people favoured trans men’s masculine faces, which match the roles of their gender identities.

Learning differentiable categorical regions with Gumbel-Softmax for person re-identification

Locating diverse body parts and perceiving part visibility are essential to person re-identification (re-ID). Most existing methods employ an extra model, e.g., pose estimation or human parsing, to locate parts, or generate pseudo labels to train the part locator incorporated with the re-ID model. In this paper, we aim at learning diverse horizontal stripes with foreground refinement to pursue pixel-level part alignment via only using person identity labels. Specifically, we proposed a Gumbel-Softmax based Differential Categorical Region (DCR) learning method and make two contributions. (1) A stripe-wise regularization. Given an image, the part locator produce part probability maps. The continuous values in the probability maps are discretized into zero or argmax value in the horizontal stripes by the Gumbel-Softmax. Gumbel-Softmax allows us to use the argmax discrete value for part diversity regularization in the forward pass, but can still estimate gradients in the backward pass. (2) A self-refinement method to suppress the background noise in the stripes. We employ a lightweight foreground perception head to produce foreground probability map with only person identity labels supervision. Benefits from discretization of the categorical stripes, we can conveniently obtain the part pseudo label by element-wise multiplying the categorical stripes with foreground probability map. Finally, DCR can locate the body parts at pixel-level and extract part-aligned representation. Experimental results on both holistic and occluded re-ID datasets confirm that our approach significantly improves the learned representation and the achieved performance is on par with the state-of-the-art methods. The code is available at https://github.com/deepalchemist/differentiable-categorical-region

Dimensions of experienced gender and prospective self-injurious thoughts and behaviors in preadolescent children: A national study

ObjectivesGender diverse youth face higher risk of engaging in self-injurious thoughts and behaviors (SITBs) compared to cisgender youth. Limitations in past research include a focus on older adolescents, an emphasis on specific gender identity labels that may not be inclusive of the range of youth gender experiences, and reliance on cross-sectional data. Thus, the current study prospectively evaluated dimensions of experienced gender in relation to first-onset SITBs among preadolescents. MethodsData were drawn from the Adolescent Brain Cognitive Development Study, a longitudinal study of youth across the United States. Youth (n = 7909) were aged 10–11 during initial assessment, and follow-up was conducted one year later. Two dimensions of experienced gender, felt-gender incongruence (not feeling aligned with the gender associated with one's sex assigned at birth) and gender non-contentedness (feeling dissatisfaction with the gender associated with one's sex assigned at birth), were assessed. Primary outcomes included non-suicidal self-injury (NSSI), suicidal ideation (SI), and suicide attempts (SA). ResultsLogistic regressions were conducted stratified by sex assigned at birth. For youth assigned female at birth, felt-gender incongruence was prospectively associated with first-onset NSSI and SI and gender non-contentedness was prospectively associated with first-onset of NSSI. For youth assigned male at birth, gender non-contentedness was prospectively associated with first-onset SI. Diverse experienced gender did not prospectively predict SA. ConclusionsDimensions of experienced gender may be associated with subsequent first-onset SITBs among preadolescents. These findings support the need for future research on risk and protective factors that may mediate or moderate this relationship.

Child sexual abuse and social identity loss: A qualitative analysis of survivors' public accounts.

Emerging evidence suggests that social identities are an important determinant of adaptation following traumatic life experiences. In this paper, we analyse accounts of people who experienced child sexual abuse. Using publicly available talk of people who waived their right to anonymity following successful conviction of perpetrators, we conducted a thematic analysis focusing on trauma-related changes in their social identities. Analysis of these accounts highlighted two themes. The first highlights the acquisition in these accounts of unwanted and damaging identity labels. The second presents child sexual abuse as a key destructive force in terms of important identity work during childhood. Discussion of this analysis centres on the pathological consequences of social identity change. Both the loss of valued identities and the acquisition of aberrant and isolating identities are experienced and constructed as devastating by those affected by child sexual abuse. This has important implications, not only for those impacted by child sexual abuse but for how abuse is discussed in society, and how it is approached by policy makers, educators and individuals working with survivors and their families.

Portrayal or Betrayal: Heteronormativity and the Realism Burden in the 2022 Disney+ Pride Collection

ABSTRACT The presence and quality of LGBTQ+ representation in film and television has important implications for viewers, especially LGBTQ+ youth. This study conducted a content analysis of the 2022 Disney+ Pride Collection, a list of movies and episodes designated by Disney as including LGBTQ+ characters and stories. This analysis examined the depiction of LGBTQ+ fictional characters, finding that Black LGBTQ+ characters were more likely to be presented as adults and in romantic relationships compared to characters of other races, suggesting that their intersecting identities influence their portrayal toward more heteronormative scripts. In what we argue is a heteronormative evolution of the butch/femme binary, lesbian characters were frequently presented on a light/dark binary. Further, in what we describe as a “realism burden,” portrayals of discrimination and LGBTQ+ identity labeling were limited to realistic fiction and adult media, and were absent from the post-gay worlds of sci-fi and fantasy.

You are not enough: Inefficient search strategies persist for self-relevant targets1

ABSTRACT Previous investigations have shown that search for an object with a unique identity is more efficient than search based on unique orientation. Here we asked whether giving an orientation target an identity label is sufficient to boost search efficiency. Participants completed two blocks of search for a line (Experiment 1) or a face (Experiment 2) with a unique orientation. Between blocks we induced an identity-based connection between the participant and search target using the self-reference effect (SRE): participants associated the target with themeselves, and distractors with “strangers.” In both experiments, search was similarly inefficient when the instructions were to search “for you” as they were in search for orientation. The results rule out an intuitively appealing explanation for the large individual differences typically observed in search efficiency, and suggest that associating a target with a more meaningful category is not in itself enough to make search more efficient.

From Deficient Masculinity to Relational Plenitude: Language and Ethics among Thirunangais in Southern India

This article engages with Tamil thirunangai transgender women’s perceptions and evaluations of masculinity and femininity among themselves and in others. Thirunangai is currently the preferred identity label among transfeminine persons in the city of Chennai in southern India. Pottai is one of many pejorative Tamil words that predate such positive linguistic assertion of Tamil transfeminine identity. In this article, I show how the word pottai is transformed into a word signaling relational plenitude, belonging, and moral selfhood among thirunangais in Chennai. I also attend to three ways in which thirunangais use the word pottai interactionally: (1) to emphasize belonging and intimacy beyond the boundaries of identity, (2) to playfully highlight genres of gendered action, and (3) to show gender’s imbrication with caste and class.

The impostor phenomenon among racially minoritised university students: ‘who knows how to get rid of this?’

ABSTRACT Less is known about the impostor phenomenon in undergraduate students and, more so, racially minoritised students in the UK. Impostorism has a constraining effect on constructing an authentic identity, leading to a feeling of phoniness. When impostorism intersects with a gendered and racially minoritised identity, individuals may face specific challenges, such as managing compound identity labels or struggling to achieve in their academic environment. This paper reports experiences of the phenomenon in Black female undergraduate students. Semi-structured focus group interviews with 10 students were analysed using inductive thematic analysis. Four themes were generated: contextual experiences of impostorism, finding sense of belonging, struggling to maintain and value an authentic self, and taming my impostor. The findings point to university environments as both barriers and enablers for taming the effect of the impostor phenomenon on academic and cultural identities and provide novel insights into an underrepresented student population.

Conceptualizing Symptom Invalidation as Experienced by Patients With Endometriosis.

The aim of this paper is to provide foundational work to standardize the conceptual definition of what I refer to as symptom invalidation by using invalidating environments and illness representations as guiding conceptual frameworks. Mixed deductive-inductive thematic analysis was used to analyze survey responses to an open-ended question gauging an invalidating interaction patients experienced with a clinician among 1038 patients with endometriosis. Dissimilarity in illness representations between patients and clinicians, as perceived by patients, occurred with feelings of invalidation. Invalidation was experienced in relationship to all identified domains of illness representations including how clinicians communicated the diagnosis (identity label), the internal (internal cause) and/or external (external cause) nature of the cause, clinicians' understanding of the timeline (timeline) and consequences (consequences), and clinicians' understanding of control over the symptoms via the efficacy of patients (self-efficacy) and coping procedures (response efficacy). Inductive analysis revealed invalidation can also be related to how clinicians communicate judgments of whether patients are presenting with ulterior motives (secondary gains). Clinicians' actions appear to compound experiences of invalidation by not having symptoms investigated (investigative experiences). Invalidating environments and illness representations serve as effective conceptual frameworks for providing a conceptual definition of symptom invalidation.

Domain generalized open-set intelligent fault diagnosis based on feature disentanglement meta-learning

Abstract Existing domain generalization-based intelligent fault diagnosis methods mainly focus on learning domain-invariant features. However, in practical scenarios, these features are difficult to extract and effectively distinguish from class-related features. Moreover, these methods often assume identical label distributions between the source and target domain, making it challenging to handle scenarios where unknown classes exist in the target domain. To address these issues, this paper proposes a domain generalized open-set intelligent fault diagnosis method based on feature disentanglement meta-learning. A binary mask feature disentanglement module is constructed to overcome the information loss caused by feature reconstruction, enabling the separation of domain-specific and class-related features. Additionally, a meta-purification loss function is defined, incorporating a correlation loss term to remove impurity features from the class-related features, and further purifying class information through feature combination pairing. The method is trained on multiple source domains using a meta-learning strategy and generalized to target domains with unknown classes. The method is utilized for bearing fault diagnosis, designing multi-task experimental scenarios under different rotational speeds, and compared with existing domain generalization methods. Experimental results show that the proposed method exhibits excellent generalization ability and effectively addresses the issue of domain generalized open-set fault diagnosis.

From other-representation to self-representation: exploring identity and activism in historical news media writing

This study addresses a significant gap in our understanding of self-representation in historical news media reporting. It focusses on one significant historical publication: the first nationally distributed Indigenous Australian newspaper written and edited by First Nations people – The Australian Abo Call: The Voice of the Aborigines (hereafter The AAC). The AAC was published in six editions in 1938, the year of the 150th anniversary of invasion of the continent now known as Australia. The corpus consists of all (non-fiction) articles from all six editions of this newspaper, which was founded, edited and largely written by Yorta Yorta man J.T. (Jack) Patten. As such, the study offers a synchronic ‘snapshot’ of a particular moment in Australian history. The study uses corpus-assisted discourse analysis to explore the linguistic construction of self-representation – how First Nations people write about themselves and the communities they represent. I proceed from inductively identifying group-based identity labels to categorising these labels in terms of their positionality in relation to ‘self’ and ‘other’. Using concordances, the study also qualitatively examines these identity labels through transitivity analysis. The results suggest that The AAC was a site of political awakening directed at both Indigenous and white Australians, calling on the former to mobilise, on the latter to listen, and on both to act. The analysis also shows that this activism sits very much within the dominant Western/Colonial frame, reflecting the historical settler-colonial context of the period in which this newspaper was published. The study has broader implications for corpus-assisted discourse analysis, by indicating the insights we gain by shifting our gaze away from ‘other’-representation in mainstream newspapers towards ‘self’-representation in community-led publications.

Beyond Translation: Exploring the Stigmatization of Rainbow Works Translation Under Frame Theory

ABSTRACT Drawing on Goffman’s frame theory, this study examines the attitudes of nine Chinese university teacher translators in translating rainbow works, ranging from hesitancy to resistance. The primary objective is to uncover the frames of stigmatization inherent in their negative attitudes toward rainbow works translation. The research clarifies the identities of perpetrators and victims in these frames leading to stigmatization. Findings indicate that various stigmatization events in rainbow works translation share a common feature—an unfavorable depiction of rainbow culture and related elements, encompassing the rainbow community, works, and translators. Perpetrators and victims vary across events, demonstrating diversity. The research interprets stigmatization in rainbow works translation at individual, institutional, and sociocultural levels. Providing a unique Chinese perspective, the study contributes to international understanding of stigmatization in a heteronormative society. It challenges traditional Chinese norms, advocates reevaluating identity labels for the rainbow community, and underscores the importance of addressing translators’ circumstances in translating rainbow works within specific societal contexts.

A Longitudinal Investigation of Trans and Nonbinary Youth Identity: Individual Processes and Family Agreement in the Trans Teen and Family Narratives Project

Few studies have focused on transgender and nonbinary youths’ (TNBY) gender development and even less well understood is how family members understand TNBY identity. The current study investigated: (a) how TNBY describe their gender identity over time, and (b) how family members understand TNBY gender identity over time. The baseline sample included 96 members of 33 families (33 TNBY, 48 cisgender caregivers, 15 siblings) from the United States; 30 families continued after Wave 1. Results indicated that 23 (77.7%) youth’s gender identity labels remained the same throughout all five waves, with seven (23.3%) youth shifting their description more than once—all youth continuing after Wave 1 who reported shifts, shifted from one TNB identity to another TNB identity. Family agreement varied across waves amongst family members regarding gender identity, gender expression, and pronoun use. Agreement and partial agreement were primarily in the High and Moderate categories across domains, with the pronouns domain demonstrating the highest level of agreement across pairings. Disagreement amongst pairings was usually not present or coded as Low, indicating greater shared understanding for families across waves and domains. Results suggest a nuanced developmental process for TNBY and their families regarding understanding of gender identity, gender expression, and pronoun use.

Constructing images of HCWs in Chinese government Weibo posts: a discourse-historical approach

This study examines the image construction of front-line healthcare workers (HCWs) in Chinese government Weibo (microblogs) during the COVID-19 pandemic. Specifically, we rely on a discourse-historical approach to analyze 1,510 posts collected from an influential government Weibo account, @healthchina (健康中国), during the first wave of the pandemic to investigate the diverse images of HCWs constructed, the discursive strategies employed, and the pragma-linguistic devices used by @healthchina. The data analyses find that Chinese HCWs are depicted as professional and competent in addressing the pandemic crisis, compassionate and caring to their patients, and responsible and devoted to public health. Two discursive strategies are found salient in HCW’s image construction—nomination and predication realized through the identity labels, attitude/judgment resources, metaphors and comparisons, pictures, and hashtags. We argue that Chinese government microbloggers intentionally constructed these images of the HCWs to elicit positive emotional responses, reinforce government trustworthiness, and foster social cohesion in the collective fight against the pandemic. This research underscores the strategic communication efforts aimed at shaping the perception of HCWs and their pivotal role in managing the pandemic.