MétaCan
Menu
Back to cohort
Record W2435453529 · doi:10.1177/0894439316653513

Introducing a Continuous Measure of Future Self-Continuity

2016· article· en· W2435453529 on OpenAlex

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

VenueSocial Science Computer Review · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsCarleton University
Fundersnot available
KeywordsClosenessMeasure (data warehouse)Social connectednessRelation (database)Computer sciencePsychologyMathematicsSocial psychologyData mining

Abstract

fetched live from OpenAlex

This article presents a continuous measure of future self-continuity (FSC-C) designed for use in web-based surveys. It allows researchers to assess on a continuous scale the similarity or connectedness that participants feel in relation to their future selves. The measure has an intuitive drag-and-drop interface, where participants can drag one circle over another circle to a certain degree of overlap to indicate closeness of the relation between their present self and their future selves. The measure is highly customizable and is therefore also attractive for researchers in other domains (e.g., to measure Inclusion of Other in the Self). In this regard, the measure is an alternative to that reported by Le, Moss, and Mashek in this journal. This article describes the motivation for the development of the measure as well as how it is constructed.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.942
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.379
Teacher spread0.343 · 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