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Record W1981788256 · doi:10.1080/13676261.2010.506527

At risk of what? Possibilities over probabilities in the study of young lives

2010· article· en· W1981788256 on OpenAlexaff
Karen Foster, Dale Spencer

Bibliographic record

VenueJournal of Youth Studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsCarleton University
Fundersnot available
KeywordsSociologyNarrativeFutures contractVocabularyPsychological resilienceLife course approachFocus (optics)PsychologyEpistemologySocial psychologyLinguistics

Abstract

fetched live from OpenAlex

This paper draws on a series of 45 interviews with recipients of social assistance between the ages of 16 and 24 to offer a critical assessment of the language of ‘risk’ and ‘resilience.’ After briefly tracing the development of this vocabulary and approach in youth research, this paper argues in line with existing critiques (Kelly 2000, te Riele 2006, France 2007) that neither risk nor resilience is an appropriate way of coming to understand young people's past, present, or future lives. Moreover, the authors argue that the language of risk and resilience commits a form of ‘symbolic violence’ (Bourdieu 1999, Frank 2002, Zizek 2008) against young people whose lives are presumably captured and finalized by this conceptual language. Instead, the authors propose that, when dealing with young people and the future, a focus on narrative and the ‘desirable futures’ interviewees envision for themselves is a more humane, and in many respects a more fruitful way of approaching the study of young lives.

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)0.021
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0100.045
Scholarly communication0.0120.020
Open science0.0010.010
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.355
Teacher spread0.312 · 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.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations71
Published2010
Admission routes1
Has abstractyes

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