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Community Research: The Lost Art of Unobtrusive Methods<sup>1</sup>

2000· article· en· W2003891060 on OpenAlexaff
Stewart Page

Bibliographic record

VenueJournal of Applied Social Psychology · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPopularityDeceptionPsychologyDoctrineResearch ethicsSocial psychologyInformed consentData collectionLawSociologySocial scienceAlternative medicinePolitical scienceMedicinePsychiatry

Abstract

fetched live from OpenAlex

The use of unobtrusive methods, with special reference to community‐oriented research, is a lost art, despite their strong recommendation by Webb, Campbell, Schwartz, &amp; Sechrest (1966) as means of supplementing reactive measures. The decline of unobtrusive measures seems to be related to the increased popularity and adherence to the doctrine of informed consent, the decrease in use of deception as a method, and the effort to conceptualize research subjects as cooperative participants. While the distaste for unobtrusive methods seems to reflect increased sensitivity toward ethics in research, the collection of partially reliable and partially valid knowledge continues, with considerable reliance on reactive measures.

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)0.022
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.585
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.007
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.228
GPT teacher head0.544
Teacher spread0.316 · 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

Citations22
Published2000
Admission routes1
Has abstractyes

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