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Record W7099332237

PUB TYPE Reports- Research/Technical (143)-- Speeches/Conference Papers (150)-- Tests/Evaluation Instruments (160)

2016· article· en· W7099332237 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicLibraries and Information Services
Canadian institutionsnot available
Fundersnot available
KeywordsParagraphViewpointsArgumentativePopulationStratified samplingProbability sampling
DOInot available

Abstract

fetched live from OpenAlex

The rationale and the methodology used in a study of high school graduates ' viewpoints on science-technology-society (STS) topics are reviewed in this paper. The study employed the instrument, Views on Science-Technology-Society (VOSTS), which required students to write an argumentative paragraph responding to one of 46 statements about an STS topic. The target population consisted of graduating high school students (N=10,800) throughout Canada. Responses from a stratified random sampling were analyzed by three researchers and the response categories were established from students ' arguments in the paragraphs. This paper primarily focuses on the instrument's format and validity and the research issues associated with this type of study. Actual results of the study are reported in related papers. Implications of the study are discussed in terms of: (1) strategies to improve understanding of student views

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0730.001

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 head0.239
GPT teacher head0.342
Teacher spread0.104 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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