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Record W2800544706 · doi:10.1177/0759106318761562

Strangers in the Field

2018· article· en· W2800544706 on OpenAlex
Alexander Weinreb, Mariano Sana, Guy Stecklov

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

VenueBulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSurvey Methodology and Nonresponse
Canadian institutionsUniversity of British Columbia
FundersNational Institutes of HealthEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentUniversity of Texas at Austin
KeywordsRespondentInterviewPsychologySituational ethicsInsiderSocial psychologyNorm (philosophy)Applied psychologySociologyPolitical science

Abstract

fetched live from OpenAlex

Evaluating a long-term methodological norm - the use of interviewers who have no prior social relationship to respondents - we compare response patterns across levels of interviewer-respondent familiarity. We differentiate three distinct levels of interviewer-respondent familiarity, based on whether the interviewer is directly acquainted with the respondent or their family, acquainted with the research setting, or is a complete outsider. We also identify three mechanisms through which variability in interviewer-respondent familiarity can affect survey responses: the effort a respondent is willing to make; their level of trust in the interviewer; and interview-specific situational factors. Using data from a methodological experiment fielded in the Dominican Republic, we then gauge the effects of each of these on a range of behavioral and attitudinal questions. Empirical results suggest that respondents expend marginally more effort in answering questions posed by insider-interviewers, and that they also lie less to insider-interviewers. Differences in responses to "trust" questions also largely favor insider-interviewers. Overall, therefore, local interviewers, including those whom, in blatant violation of the stranger-interviewer norm, have a prior relationship with the respondent, collect superior data on some items. And on almost no item do they collect data that are measurably worse.

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)0.277
metaresearch head score (Gemma)0.424
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2770.424
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.010
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.436
GPT teacher head0.507
Teacher spread0.071 · 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