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Record W2128738510 · doi:10.1109/tpc.2010.2052852

Employee Reactions to Paper and Electronic Surveys: An Experimental Comparison

2010· article· en· W2128738510 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

VenueIEEE Transactions on Professional Communication · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsConcordia University
Fundersnot available
KeywordsFeelingPsychologyQuality (philosophy)Survey instrumentField (mathematics)Survey data collectionApplied psychologySocial psychologyStatisticsMathematics

Abstract

fetched live from OpenAlex

Using a within-subjects field experiment, we tested the differences between paper-based and electronic employee surveys. Employees of a large organization were invited to respond to a paper survey as well as an identical electronic survey. Results from 134 employees who completed both questionnaires indicated that electronic surveys were seen as marginally easier to use and more enjoyable than paper surveys. However, the paper-based questionnaires produced a higher response rate. The self-reported likelihood that participants would respond to similar questionnaires in the future did not differ between the two formats. After comparing the answers on survey items that measured feelings of well-being and spending patterns, data quality also appeared to be equivalent across the two formats. Conceptual issues, as well as the implications for managers who are administering employee surveys, are discussed.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.709
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.111
GPT teacher head0.441
Teacher spread0.330 · 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