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Record W2128788014 · doi:10.1177/0165025413477007

Examining the developmental dynamics between achievement strategies and different literacy skills

2013· article· en· W2128788014 on OpenAlexaff
George K. Georgiou, George Manolitsis, Xiao Zhang, Rauno Parrila, Jari-Erik Nurmi

Bibliographic record

VenueInternational Journal of Behavioral Development · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyFluencyDevelopmental psychologyLiteracySpellingReading comprehensionTask (project management)Reading (process)ComprehensionAcademic achievementMathematics educationPedagogy

Abstract

fetched live from OpenAlex

We examined the developmental dynamics between task-avoidant behavior and different literacy outcomes, and possible precursors of task-avoidant behavior. Seventy Greek children were followed from Grade 4 until Grade 6 and were assessed every year on reading fluency, spelling, and reading comprehension. The teachers assessed the children’s achievement strategies at all testing times. In addition, in Grade 4, the children responded to a task value questionnaire and the parents reported their beliefs and expectations about their children’s academic performance. The results revealed that task avoidance was reciprocally related only to reading comprehension. In addition, only parental beliefs predicted task avoidance. These findings complement those of previous studies in transparent orthographies and suggest that the role of task avoidance on literacy development depends on the time when the literacy skills are assessed and the type of literacy outcome.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.035
GPT teacher head0.341
Teacher spread0.306 · 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 designObservational
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

Citations16
Published2013
Admission routes1
Has abstractyes

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