Who I Am: The Meaning of Early Adolescents’ Most Valued Activities and Relationships, and Implications for Self-Concept Research

Self-concept research in early adolescence typically measures young people’s self-perceptions of competence in specific, adult-defined domains. However, studies have rarely explored young people’s own views of valued self-concept factors and their meanings. For two major self domains, the active and the social self, this mixed-methods study identified factors valued most by 526 young people from socioeconomically diverse backgrounds in Ireland (10-12 years), and explored the meanings associated with these in a stratified subsample (n = 99). Findings indicate that self-concept scales for early adolescence omit active and social self factors and meanings valued by young people, raising questions about content validity of scales in these domains. Findings also suggest scales may under-represent girls’ active and social selves; focus too much on some school-based competencies; and, in omitting intrinsically salient self domains and meanings, may focus more on contingent (extrinsic) rather than true (intrinsic) self-esteem

A Three-Dimensional Taxonomy of Achievement Emotions

We present a three-dimensional taxonomy of achievement emotions that considers valence, arousal, and object focus as core features of emotions occurring in achievement settings. By distinguishing between positive and negative emotions (valence), activating and deactivating emotions (arousal), and activity emotions, prospective outcome emotions, and retrospective outcome emotions (object focus), the taxonomy has a 2 × 2 × 3 structure representing 12 groups of achievement emotions. In four studies across different countries (N = 330, 235, 323, and 269 participants in Canada, the US, Germany, and the UK, respectively), we investigated the empirical robustness of the taxonomy in educational (Studies 1-3) and work settings (Study 4). An expanded version of the Achievement Emotions Questionnaire was used to assess 12 key emotions representing the taxonomy. Consistently across the four studies, findings from multilevel facet analysis and structural equation modeling documented the importance of the three dimensions for explaining achievement emotions. In addition, based on hypotheses about relations with external variables, the findings show clear links of the emotions with important antecedents and outcomes. The Big Five personality traits, appraisals of control and value, and context perceptions were predictors of the emotions. The 12 emotions, in turn, were related to participants’ use of strategies, cognitive performance, and self-reported health problems. Taken together, the findings provide robust evidence for the unique positions of different achievement emotions in the proposed taxonomy, as well as unique patterns of relations with external variables. Directions for future research and implications for policy and practice are discussed

The HITRAN2020 Molecular Spectroscopic Database

The HITRAN database is a compilation of molecular spectroscopic parameters. It was established in the early 1970s and is used by various computer codes to predict and simulate the transmission and emission of light in gaseous media (with an emphasis on terrestrial and planetary atmospheres). The HITRAN compilation is composed of five major components: the line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, experimental infrared absorption cross-sections (for molecules where it is not yet feasible for representation in a line-by-line form), collision-induced absorption data, aerosol indices of refraction, and general tables (including partition sums) that apply globally to the data. This paper describes the contents of the 2020 quadrennial edition of HITRAN. The HITRAN2020 edition takes advantage of recent experimental and theoretical data that were meticulously validated, in particular, against laboratory and atmospheric spectra. The new edition replaces the previous HITRAN edition of 2016 (including its updates during the intervening years). All five components of HITRAN have undergone major updates. In particular, the extent of the updates in the HITRAN2020 edition range from updating a few lines of specific molecules to complete replacements of the lists, and also the introduction of additional isotopologues and new (to HITRAN) molecules: SO, CH3F, GeH4, CS2, CH3I and NF3. Many new vibrational bands were added, extending the spectral coverage and completeness of the line lists. Also, the accuracy of the parameters for major atmospheric absorbers has been increased substantially, often featuring sub-percent uncertainties. Broadening parameters associated with the ambient pressure of water vapor were introduced to HITRAN for the first time and are now available for several molecules. The HITRAN2020 edition continues to take advantage of the relational structure and efficient interface available at www.hitran.org and the HITRAN Application Programming Interface (HAPI). The functionality of both tools has been extended for the new edition

The HITRAN2020 molecular spectroscopic database

The HITRAN database is a compilation of molecular spectroscopic parameters. It was established in the early 1970s and is used by various computer codes to predict and simulate the transmission and emission of light in gaseous media (with an emphasis on terrestrial and planetary atmospheres). The HITRAN compilation is composed of five major components: the line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, experimental infrared absorption cross-sections (for molecules where it is not yet feasible for representation in a line-by-line form), collision-induced absorption data, aerosol indices of refraction, and general tables (including partition sums) that apply globally to the data. This paper describes the contents of the 2020 quadrennial edition of HITRAN. The HITRAN2020 edition takes advantage of recent experimental and theoretical data that were meticulously validated, in particular, against laboratory and atmospheric spectra. The new edition replaces the previous HITRAN edition of 2016 (including its updates during the intervening years). All five components of HITRAN have undergone major updates. In particular, the extent of the updates in the HITRAN2020 edition range from updating a few lines of specific molecules to complete replacements of the lists, and also the introduction of additional isotopologues and new (to HITRAN) molecules: SO, CH3F, GeH4, CS2, CH3I and NF3. Many new vibrational bands were added, extending the spectral coverage and completeness of the line lists. Also, the accuracy of the parameters for major atmospheric absorbers has been increased substantially, often featuring sub-percent uncertainties. Broadening parameters associated with the ambient pressure of water vapor were introduced to HITRAN for the first time and are now available for several molecules. The HITRAN2020 edition continues to take advantage of the relational structure and efficient interface available at www.hitran.org and the HITRAN Application Programming Interface (HAPI). The functionality of both tools has been extended for the new edition

The Music Self-Perception Inventory: Development of parallel forms A and B

Music self-concept integrates perceptions, beliefs, and self-schemas about a person’s musical abilities and potential. Like other self-concept dimensions, it is multifaceted, hierarchically organized and has implications for motivation toward musical practice. The Music Self-Perception Inventory (MUSPI) is a theoretically-based instrument assessing six specific music self-concept dimensions, as well as global music self-concept. Nonetheless, its applicability is limited by its length (84 items) and by the fact that it does not provide a way to control for consistency biases in the context of repeated measurement In this study, we developed and validated two parallel versions (A and B) of the MUSPI, and showed that both yielded equivalent psychometric properties to the original, and were fully equivalent to one another. We also tested whether the MUSPI-A and MUSPI-B psychometric properties generalized (were invariant) across gender and grade-differentiated subgroups. Finally, we examined the convergent validity of the MUSPI-A and MUSPI-B. Results highlighted the psychometric soundness, and equivalence, of the various MUSPI versions on all criteria, and showed that they presented patterns of associations with other constructs equivalent to that observed with the original MUSPI