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We present a theoretical model of reappropriation—taking possession of a slur previously used exclusively by dominant groups to reinforce another group's lesser status. Ten experiments tested this model and established a reciprocal relationship between power and self-labeling with a derogatory group term. We first investigated precursors to self-labeling: Group, but not individual, power increased participants' willingness to label themselves with a derogatory term for their group. We then examined the consequences of such self-labeling for both the self and observers. Self-labelers felt more powerful after self-labeling, and observers perceived them and their group as more powerful. Finally, these labels were evaluated less negatively after self-labeling, and this attenuation of stigma was mediated by perceived power. These effects occurred only for derogatory terms (e.g., queer, bitch), and not for descriptive (e.g., woman) or majority-group (e.g., straight) labels. These results suggest that self-labeling with a derogatory label can weaken the label's stigmatizing force.

Ethnic/racial self-labeling represents one’s knowledge of and preference for ethnic/racial group membership, which is related to, but distinguishable from, ethnic/racial identity. This study examined the development of ethnic/racial self-labeling over time by including the concept of elaboration among a diverse sample of 297 adolescents (Time 1 mean age 14.75, 67% female, 37.4% Asian or Asian American, 10.4% Black, African American, or West Indian, 23.2% Hispanic or Latinx, 24.2% White, 4.4% other). Growth mixture modeling revealed two distinct patterns—low and high self-labeling elaboration from freshman to sophomore year of high school. Based on logistic regression analyses, the level of self-labeling elaboration was generally low among the adolescents who were foreign-born, reported low levels of ethnic/racial identity exploration, or attended highly diverse schools. We also found a person-by-context interaction where the impact of school diversity varied for foreign-born and native-born adolescents (b = 12.81, SE = 6.30, p < 0.05) and by the level of ethnic/racial identity commitment (b = 14.32, SE = 6.65, p < 0.05). These findings suggest varying patterns in ethnic/racial self-labeling elaboration among adolescents from diverse backgrounds and their linkage to individual and contextual factors.

To explore how employees understand work-related sexual harassment and label their experience. This study is based on 13 semi-structured in-depth interviews with employees exposed to workplace sexual harassment. We analysed the data using a thematic approach drawing on frameworks of sensemaking in organizations. We identified four major themes. The first two themes, and , outline the interviewees' definitions of the two terms \"sexual harassment\" and \"unwanted sexual harassment\" and reveal the challenges of labelling sexually harassing behaviours at work. The last two themes; and , explain the sensemaking process, i.e., how the interviewees come to understand and label their experience. The analysis showed that the interviewees related sexual harassment with physical, coercive, and intentional behaviours, whereas unwanted sexual attention was seen as less severe and less intentional. The interviewees often doubted how to label their experience, and making sense of one´s experience could take years. Self-labelling is inherently a social process, and the validation and rejection of others play an important role. Finally, the #MeToo movement constituted a turning point for several interviewees' understandings of events.

Detainees enact a \"self\" that is faced with the prejudices and stereotypes of the crime for which that detainee was convicted. Of all inmates, sex offenders face the greatest risk of receiving social condemnation alongside their prison sentence. This empirical study worked with 32 male sex offenders over 18 years old that were housed in the \"protected\" unit of the Due Palazzi. The following analysis explores how these men are required to manage their \"self,\" hetero-narrations, perception of everyday interactions in the protected unit, and conceptions about the rehabilitation path. Moreover, the detainees' view on the prison's strategic opportunities for promoting effective change in their condition and identity are also examined. Discourse analysis applied to an open answer questionnaire showed that, rather than facing the stigma assigned to them, the detainees tend to minimize the importance of storytelling and construct alternative biographies to share with other inmates. Managing narratives allows the sex offenders to distance themselves from the perceived threats of living with other detainees; however, it also prevents the re-signification of their offenses. As such, the rules of \"secrecy\" must be considered by both qualitative researchers who conduct studies in prisons and prison administrators who plan the housing and treatment of sex offenders.

Disaggregated data on housing and household economic conditions, particularly in developing countries, are often inaccessible to urban planners and local users, and conducting independent in-person surveys is prohibitively expensive. This impedes the development of precisely informed policies and targeted infrastructure investments, services, and incentives that are essential for fostering equitable and sustainable cities. Using Kigali and Musanze cities in Rwanda, this study introduces a novel deep learning-based approach that combines limited expert annotation, self-training, and instance image segmentation to generate building-level housing wealth data. Our experiment included state-of-the-art instance segmentation based on You Only Look Once (YOLO) and Masked-attention Mask Transformer (Mask2former) models. To check the validity of the predictions, over ten thousand samples from the official cadastre-based property taxation database were used to evaluate whether the observed patterns in actual property values align with the model's predictions. Importantly, our method successfully detected approximately 70% of the existing buildings within their respective perceived wealth classes. Buildings predicted to belong to the high-wealth class exhibited mean property values 2.5-times higher in Kigali and 1.7-times higher in Musanze than those classified as low-wealth, thereby demonstrating the model's ability to capture spatial patterns of housing wealth. The predicted maps reveal that housing wealth growth in urban cores parallels increased low-wealth housing in peri-urban areas, a likely result of gentrification, an insight that could inform more inclusive urban development strategies and support policies aimed at curbing urban sprawl. Our findings demonstrate that combining minimal expert labeling of economically meaningful visual features with self-training and multi-class instance segmentation offers an effective and rapid approach for generating precise planning data in contexts that lack detailed local census information. Moreover, while leveraging advanced deep networks, our methodology was designed to be simple and easily replicable.

Deviant or stigmatizing labels are associated with various negative outcomes. Although self-labeling theory proposes that one can self-label as deviant without first being labeled by others, most labeling research focuses on people whom others have already labeled. Using the case of undergraduates aged twenty-five and older, I identify three subtle forms of interaction—contextual dissonance, reminder cues, and third-party communication—that trigger self-labeling and are associated with negative reactions, even absent others' direct negative feedback or prior labeling. I also show that each form of interaction may systematically relate to specific kinds of negative reactions. I discuss possible reasons for these patterns, as well as how these findings may affect self-labeling theory and policymaking decisions in higher education.

Stigma devalues individuals and groups, producing social and economic disadvantages through two distinct but reinforcing processes: direct discrimination (e.g., a White person not hiring a Black person based on race) and stigma internalization (e.g., women believing men are more qualified for leadership positions). We review strategies that individuals can use to not only cope with but also challenge their stigma. We discuss how attempts to escape stigma can be effective at the individual level but may leave the stigma itself unchanged or even reinforced. We then identify two ways individuals can reappropriate and take ownership of their stigma to weaken it: reframing and self-labeling. Reframing highlights stereotypic characteristics as assets rather than liabilities—for example, framing stereotypically feminine traits (e.g., social intelligence) as essential for effective negotiations or leadership. Self-labeling involves referring to oneself with a group slur. We discuss ways to utilize these reappropriation strategies as well as how to handle potential pitfalls.

Keeping the performance of language technologies optimal as time passes is of great practical interest. We study temporal effects on model performance on downstream language tasks, establishing a nuanced terminology for such discussion and identifying factors essential to conduct a robust study. We present experiments for several tasks in English where the label correctness is not dependent on time and demonstrate the importance of distinguishing between temporal model deterioration and temporal domain adaptation for systems using pre-trained representations. We find that, depending on the task, temporal model deterioration is not necessarily a concern. Temporal domain adaptation, however, is beneficial in all cases, with better performance for a given time period possible when the system is trained on temporally more recent data. Therefore, we also examine the efficacy of two approaches for temporal domain adaptation without human annotations on new data. Self-labeling shows consistent improvement and notably, for named entity recognition, leads to better temporal adaptation than even human annotations.

The primary label for people who are sexually attracted to children (“pedophile”) is conflated with sexual offending behavior and tainted with stigma. In the present pre-registered mixed-method study, we therefore investigated attitudes and preferences regarding \"pedophile/hebephile\" and other labels among 286 people who report a stronger or equally strong sexual attraction to prepubescent and pubescent children than to adults. Overall, quantitative data showed acceptance of “pedophile/hebephile” as well as a range of alternative labels in a personal ( Labeling Oneself ) and a professional context ( Being Labeled by Others ). “Minor-attracted person” and “pedophile/hebephile” received generally higher support than other terms and appeared to be least divisive across three major online fora. Qualitative data revealed four themes: “Contested self-labels,” “Person-first language and pathologizing sexuality/identity,” “Stigma and shame,” and “Reclaiming the pedophile label.” Our results allow deeper insight into reasons for adopting certain labels over others, as well as difficulties of finding a non-stigmatizing label. We discuss limitations of the study and practical implications for clinical and research contexts.

Bioorthogonal click-reactions represent ideal means for labeling biomolecules selectively and specifically with suitable small synthetic dyes. Genetic code expansion (GCE) technology enables efficient site-selective installation of bioorthogonal handles onto proteins of interest (POIs). Incorporation of bioorthogonalized non-canonical amino acids is a minimally perturbing means of enabling the study of proteins in their native environment. The growing demand for the multiple modification of POIs has triggered the quest for developing orthogonal bioorthogonal reactions that allow simultaneous modification of biomolecules. The recently reported bioorthogonal [4 + 1] cycloaddition reaction of bulky tetrazines and sterically demanding isonitriles has prompted us to develop a non-canonical amino acid (ncAA) bearing a suitable isonitrile function. Herein we disclose the synthesis and genetic incorporation of this ncAA together with studies aiming at assessing the mutual orthogonality between its reaction with bulky tetrazines and the inverse electron demand Diels–Alder (IEDDA) reaction of bicyclononyne (BCN) and tetrazine. Results showed that the new ncAA, bulky-isonitrile-carbamate-lysine (BICK) is efficiently and specifically incorporated into proteins by genetic code expansion, and despite the slow [4 + 1] cycloaddition, enables the labeling of outer membrane receptors such as insulin receptor (IR) with a membrane-impermeable dye. Furthermore, double labeling of protein structures in live and fixed mammalian cells was achieved using the mutually orthogonal bioorthogonal IEDDA and [4 + 1] cycloaddition reaction pair, by introducing BICK through GCE and BCN through a HaloTag technique.