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Record W2034944613 · doi:10.1080/02702710500400495

Didn't You Run the Spell Checker? Effects of Type of Spelling Error and Use of a Spell Checker on Perceptions of the Author

2005· article· en· W2034944613 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReading Psychology · 2005
Typearticle
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSpellingSpellHomophonePerceptionQuality (philosophy)PsychologyComputer scienceWord (group theory)LinguisticsCognitive psychologySociology

Abstract

fetched live from OpenAlex

We investigated expectations regarding a writer's responsibility to proofread text for spelling errors when using a word processor. Undergraduate students read an essay and completed a questionnaire regarding their perceptions of the author and the quality of the essay. We manipulated type of spelling error (no error, homophone error, non-homophone error) and information provided about the author's use of a spell checker (no information, author did not use a spell checker, author did use a spell checker). Participants' perceptions of the author's abilities and the quality of the essay suffered when the essay contained non-homophone spelling errors—errors that are typically flagged by a spell checker. Further, participants reported that they would be most likely to blame the writer rather than the spell checker for spelling errors contained in the text. These findings suggest that perceptions of both an author's abilities and the written products are affected by spelling errors. Even when supportive tools are available, the responsibility for producing error-free text remains with the author.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.249

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 science0.0010.000
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 head0.058
GPT teacher head0.351
Teacher spread0.293 · 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