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Record W4248382567 · doi:10.3138/cmlr.57.4.590

Reading Hypertext: Higher-Level Processes

2001· article· en· W4248382567 on OpenAlexvenueno aff
Joel Walz

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2001
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsHypertextReading (process)Meaning (existential)Computer scienceAllusionWorld Wide WebPerspective (graphical)MultimediaLinguisticsPsychologyArtificial intelligence

Abstract

fetched live from OpenAlex

In a previous issue of this journal (2001a, vol. 57, no. 3), an application of reading theory to WWW documents ('hypertext') revealed two problems for beginning learners: reading an electronic format and deciphering the language used in Web pages. A third major difficulty for readers is content; it requires higher-level reading processes, which call on the reader's store of knowledge. This article proposes pedagogical solutions to these problems, including a study of Uniform Resource Locators (URLs) to enhance predictions, the analysis of visuals that support the meaning of the text, and the conversion of search engine summaries into pre-reading activities to activate schemata. Three additional skills related to content are the understanding of cultural allusions, critical reading, and the ability to read extensively. Cultural allusions are frequent in hypertext, especially in personal home pages. Readers can ask pertinent questions based on surrounding text, and they can research an allusion online to determine meaning. Critical reading is a necessary skill to develop when reading hypertext, since much information is incorrect or biased. The identification of sources and text type to gain perspective on the author's intended message is recommended. The necessity for extensive reading with the WWW requires ways of helping students choose appropriate sites and of evaluating their work in order to promote reading for meaning.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0320.001

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 head0.032
GPT teacher head0.282
Teacher spread0.250 · 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.

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

Citations4
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Modern Language Review/ La Revue canadienne des langues vivantesSame topicSecond Language Acquisition and LearningFrench-language works237,207