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Record W4380625463 · doi:10.31234/osf.io/tnaxb

State versus trait conceptualizations of parental monitoring: a formulation and review

2023· preprint· en· W4380625463 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
FundersNational Institute on Drug AbuseNational Institute on Alcohol Abuse and AlcoholismCanadian Institutes of Health Research
KeywordsConceptualizationTraitPsychologyDevelopmental psychologyState (computer science)Social psychologyComputer science

Abstract

fetched live from OpenAlex

We propose and evaluate two competing conceptualizations of parental monitoring of youths’ activities—a trait conceptualization and a state conceptualization. In a trait conceptualization, the level of monitoring is largely stable over time within families and youth behavior at any given moment is affected by the overall level of monitoring over a long period (e.g., past few months, past year). In a state conceptualization, the level of monitoring varies substantially from moment-to-moment and youth behavior at any given moment is affected by the current, acute level of monitoring. The trait and state conceptualizations have contrasting implications for designing research, identifying causal mechanisms, intervening with families to improve monitoring, and anticipating how youth will respond to temporary changes in the level of monitoring. Reviewing the literature, we find that most prior research has implicitly adopted the trait conceptualization, despite there being little theoretical analysis or empirical evidence to justify the choice of one conceptualization over the other. No study has reported on the day-to- day stability of monitoring, though a handful have reported low day-to-day stability for closely related constructs (e.g., parental knowledge). Too few studies have tested shorter-term or acute effects of monitoring to make strong conclusions about the timescale of effects, though available evidence suggests there is no effect of overall monitoring measured today on youth outcomes measured 6-12 months later. We conclude that whether monitoring is best conceptualized as a trait or state remains an important open question.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

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

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 head0.170
GPT teacher head0.406
Teacher spread0.236 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations9
Published2023
Admission routes1
Has abstractyes

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