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Record W7146963044 · doi:10.65301/ijcd.2025.15.3.4.10

Book Review: From Likes to Lives: Unravelling the Impact of Social Networking Sites on Youth

2025· article· W7146963044 on OpenAlexaff
Surbhi Tandon, Mr Sidharth Verma, Ramesh Kumar, Tripathi The

Bibliographic record

VenueInternational Journal of Communication Development · 2025
Typearticle
Language
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsCouncil of Ministers of Education
Fundersnot available
KeywordsSocial mediaNew delhiPoliticsFoundation (evidence)Consumption (sociology)Civic engagement

Abstract

fetched live from OpenAlex

The book provides an overview of the comprehensive study undertaken by the researchers among youth in Delhi and Varanasi regarding their social media usage, its impacts, potential for positive utilization, and perceptible threats that the techno-social networks pose. The book is divided into six chapters with each of them providing a strong foundation and theoretical precepts to understand the multifaceted nature of social networking sites. The book concerns itself with both the individual behavior and collective experiences of the youth in important areas of inquiry such as civic engagement and evolving forms of democratic participation, political communication, e-governance, and digital education. The book's strength lies in providing a comprehensive comparative analysis of the media consumption patterns of the youth in Delhi and Varanasi in the rapidly evolving media scape of the country.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0140.006

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 head0.053
GPT teacher head0.388
Teacher spread0.336 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2025
Admission routes1
Has abstractyes

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