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Record W2135153892 · doi:10.1598/jaal.50.2.6

Resistance, Struggle, and the Adolescent Reader

2006· article· en· W2135153892 on OpenAlexaff
Kimberly Lenters

Bibliographic record

VenueJournal of Adolescent & Adult Literacy · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsReading (process)Resistance (ecology)PsychologyActive listeningAgency (philosophy)LiteracyIdentity (music)PedagogyPerspective (graphical)Reading motivationSociologyCommunicationLinguisticsComputer scienceSocial science

Abstract

fetched live from OpenAlex

An important research paradigm applied to the study of adolescent resistance to reading—listening to student voice—has yielded rich information regarding adolescent literacy practices, adolescent agency, and adolescent identity as components of resistance to reading. Instructional perspectives of teachers and researchers also serve to shed light on the phenomenon and provide insight on better understanding the interplay between adolescent resistance to reading and struggle with literacy acquisition. For some teachers, the “problem” with adolescent readers and resistance to reading lies outside their sphere of responsibility or influence; however, adolescent and researcher voices provide a somewhat different perspective. Understanding and addressing the disjuncture becomes particularly important when addressing the instructional needs of struggling adolescent readers: Readers who resist reading risk becoming readers who struggle, and those who already struggle with reading miss important opportunities for improvement through interaction with text. Instructional implications aimed at addressing resistance to in‐school reading are also presented.

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.006
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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 designQualitative
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

Citations80
Published2006
Admission routes1
Has abstractyes

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