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Record W4379876035 · doi:10.1177/21582440231179204

The Perspectives of Senior Researchers in Applied Disciplines on the Current State of Developmental Attachment Research: An Interview Study

2023· article· en· W4379876035 on OpenAlexaff
Alissa Mann, Megan M. Thompson, Sarah Foster, Helen Beckwith, Sheri Madigan, Pasco Fearon, Carlo Schuengel, Robbie Duschinsky

Bibliographic record

VenueSAGE Open · 2023
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyDevelopmental ScienceAttachment theoryDevelopmental psychologyQualitative researchPsychological interventionStrengths and weaknessesPerspective (graphical)PerceptionBiomedicineDevelopmental stage theoriesSocial psychologySociologySocial science

Abstract

fetched live from OpenAlex

Based on interviews with leading researchers and researcher-clinicians in fields allied to attachment research, this paper describes participants’ perceptions of contemporary attachment research in the developmental tradition. Semi-structured qualitative interviews were conducted with 13 research leaders in applied disciplines cognate to attachment research. Participants perceived attachment research as having played a foundational role for developmental science, including highlighting the importance of a developmental perspective and attention to early caregiving experiences. They also identified important contemporary strengths in developmental attachment research, including the observational acuity and insightfulness of its measures, its attention to dyadic processes in contrast to much of biomedicine, the development of a number of attachment-based interventions with well-articulated mechanisms of action, and the capacity of developmental attachment concepts to resonate with clinical and popular audiences. However, participants suggested that the developmental tradition is also perceived as having a comparatively high “cost of entry,” and consequently they warned that it has become somewhat separated from wider developmental science, with its growing prominence of biological research, scalability of methods, and less reliance on theory. Participants perceived both strengths and weaknesses to contemporary developmental attachment research. However they felt that the classic concerns of developmental attachment research were placing the field potentially at odds with current trends in developmental science.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.066
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.067
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0160.015
Scholarly communication0.0120.008
Open science0.0020.014
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0020.001

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 head0.376
GPT teacher head0.570
Teacher spread0.194 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainEvaluation
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

Citations3
Published2023
Admission routes1
Has abstractyes

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