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Record W4312305283 · doi:10.4103/0019-5545.341915

Workshop Compiled

2022· article· en· W4312305283 on OpenAlexaff
Alka A. Subramanyam, Prajakta Patkar, Samiksha Sahu, Abhilasha Tyagi, Fiona Mehta

Bibliographic record

VenueIndian Journal of Psychiatry · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsAnxietyPsychologyPandemicSocial isolationCoronavirus disease 2019 (COVID-19)Mental illnessEveryday lifeDevelopmental psychologyPsychiatryMental healthMedicinePolitical scienceDisease

Abstract

fetched live from OpenAlex

Aim: 1. To revisit “normalcy” as we understood. 2. To understand digital natives and their norms. 3. To explore the impact of the pandemic on the above. Outline: The pandemic was a challenging time for everyone which had an effect on everyday life of multiple individuals. However, the trajectory of the psychological, social and cultural development of the developing minds took a completely different turn. The additional screen use was somewhat inevitable because everything right from personal life to education turned online but on the same hand the prevalence of problematic screentime including social media and gaming increased exponentially. (1) Youth with anxiety, depression, psychotic illness and neurodevelopmental disorders were especially vulnerable to worsening or re-emergence of their symptoms in the times of changing uncertainties. (2) Along with contact restrictions and isolation, there was increased report of parental mental illness, domestic violence and child maltreatment which had a direct effect on the development of the children’s minds. (3) Although there is lack of significant evidence, increased incidence of cases of gender dysphoria and confused sexuality has been noticed due to decreased social exploration and increased exposure to online content in this regard. There are a myriad of changes which has happened in the past two decades because of advent of technology which are both positive and negative, but this Pandemic has amplified both. This workshop will consist of presentations, oral discussions and group activities to understand these changing trends in the development of young minds during the pandemic. References 1. Paschke, Kerstin, Maria Isabella Austermann, Kathrin Simon-Kutscher, and Rainer Thomasius. “Adolescent gaming and social media usage before and during the COVID-19 pandemic.” Sucht (2021). 2. Becker, Stephen P., and Alice M. Gregory. “Editorial Perspective: Perils and promise for child and adolescent sleep and associated psychopathology during the COVID-19 pandemic.” (2020): 757-759. 3. Fegert, Jörg M., Benedetto Vitiello, Paul L. Plener, and Vera Clemens. “Challenges and burden of the Coronavirus 2019 (COVID-19) pandemic for child and adolescent mental health: a narrative review to highlight clinical and research needs in the acute phase and the long return to normality.” Child and adolescent psychiatry and mental health 14 (2020): 1-11.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.287
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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