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Record W28897192

Elective Reading Course for Grades 7-9.

2000· article· en· W28897192 on OpenAlexaboutno aff
Kathy Thomson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)NewspaperPsychologyMedical educationMathematics educationComputer sciencePedagogySociologyMedia studiesMedicinePolitical science
DOInot available

Abstract

fetched live from OpenAlex

The program of studies for a reading elective course for avid or potentially avid readers at the junior high school level contained in this guide represents an attempt to address problems experienced by-Young adult readers. The program would provide time for them to read, and it would allow students the opportunity to value reading whether it be periodicals, newspapers, novels. Additionally, the program would allow students to progress through the stages of reading that would enhance their chances of becoming lifelong readers, and it would allow them the opportunity to discuss what they are reading and extend themselves in the process. Most importantly, the program will also allow students to make their own reading selections, an issue that is often overlooked in language arts classes. The program guide contains the following sections: General Introduction; Course Assessment; Community Service Projects; On-going Individual Reading Assignments; Award Winning Books; Film/Novel Study; Book Challenges and Censorship; and Author Interviews. (Contains 23 references.) (NKA) Reproductions supplied by EDRS are the best that can be made from the original document. Elective Reading Course for Grades 7-9 1 Elective Reading Course for Grades 7-9 Kathy Thomson University of Alberta, Edmonton, Alberta U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) This document has been reproduced as received from the person or organization originating it. Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this tzt document do not necessarily represent official OERI position or policy. O ci) C.) BEST COPY AVAILABLE 1-02 1 PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.533
Threshold uncertainty score0.132

Codex and Gemma teacher scores by category

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

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 head0.029
GPT teacher head0.356
Teacher spread0.327 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
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

Citations0
Published2000
Admission routes1
Has abstractyes

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