DEVELOPING A NOMOLOGICAL NETWORK FOR INTERVIEW STRUCTURE: ANTECEDENTS AND CONSEQUENCES OF THE STRUCTURED SELECTION INTERVIEW
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.
Bibliographic record
Abstract
A review by Campion, Palmer, and Campion (1997) identified 15 elements of interview structure and made predictions regarding how applicants and interviewers might react to these elements. In this 2‐sample field survey of 812 interviewees and 592 interviewers from over 502 organizations, interview structure was best described by 4 dimensions: (a) Questioning Consistency, (b) Evaluation Standardization, (c) Question Sophistication, and (d) Rapport Building. Interviewers with formal training and those with a selection rather than recruiting focus employed higher levels of interview structure. In addition, reactions to increased structure were mixed. Both higher structure (Question Sophistication) and lower structure (Rapport Building) were positively related to interviewer reactions. Less than 34% of interviewers had any formal interview training. However, interviewers were confident that they could identify the best candidates regardless of the amount of interview structure employed. Applicants reacted negatively to the increased perceived difficulty of structured interviews, but perceptions of procedural justice were not affected by interview structure.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it