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.
fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.
VenueReference Reviews · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
FundersUniversity of Illinois at ChicagoUniversity of California, IrvineLingnan UniversityStockholms UniversitetUniversidade do MinhoNational Taiwan Normal UniversitySyddansk UniversitetUniversità Cattolica del Sacro CuoreUniversity of HaifaCentre National de la Recherche ScientifiqueUniversiti Putra MalaysiaOrta Doğu Teknik ÜniversitesiVrije Universiteit AmsterdamLomonosov Moscow State UniversityRadboud UniversiteitHarvard Graduate School of EducationUniversity of AucklandInstitut National de la Santé et de la Recherche MédicaleGriffith UniversityCenter for Advanced Study, University of Illinois at Urbana-ChampaignKU LeuvenPomona CollegeUniversity of New South WalesAnadolu ÜniversitesiMonash UniversityUniversity College CorkMassey UniversityAustralian Catholic UniversityCardiff UniversityUniversity of SussexUniversity of California, Los AngelesUniversità degli Studi di MilanoSaint Louis UniversityManchester Metropolitan UniversityUniversity College LondonUniversity of SouthamptonMax Planck Instituut voor PsycholinguïstiekKent State UniversityWellcome TrustUniversity of OxfordMcMaster UniversityNorges Teknisk-Naturvitenskapelige UniversitetIndiana University BloomingtonUniversidade Estadual de CampinasUniversity of BernCarnegie Mellon UniversityRobert Gordon UniversityiMindsImperial College LondonUniversity of MemphisUniversity of OklahomaYork UniversityQueen's UniversityUniversity of MiamiUniversity of Central FloridaNorthwestern UniversityUniversity of MissouriUniversiteit UtrechtTU Graz, Internationale Beziehungen und MobilitätsprogrammeUniversité de LyonUniversity of Technology SydneyIllinois State UniversityUniversity of ConnecticutMcGill UniversityUniversität SalzburgUniversität des SaarlandesUniversiteit GentWorcester Polytechnic InstituteBrown UniversityQueensland Brain InstituteUniversity of Wisconsin-MadisonDepartment of Epidemiology, Biostatistics and Occupational Health, McGill UniversityUtah State UniversityPrinceton UniversityUniversity of Illinois at Urbana-ChampaignUniversity of GeorgiaPennsylvania State UniversityWestern Michigan UniversityHarvard UniversityUniversity of Pennsylvania
KeywordsEncyclopediaLibrary sciencePsychologySociologyComputer science
Abstract
fetched live from OpenAlexThe Encyclopedia of the Sciences of Learning is the first major reference work in the growing and highly visible field of learning sciences. It brings together definitional entries from scholars who represent the breath of this interdisciplinary area of study, teaching, and practice: biology, neuroscience, psychology, computer and information science, philosophy, anthropology, sociology, education, and a range of narrower technical and applied fields. Given the increasing amount of scholarly and popular attention to the dimensions and questions of human learning, it’s important to note that this encyclopedia devotes equal time to animal and machine learning as well; this is a significant difference that sets it apart from previously-published reference works on educational psychology. It also maintains an international sensibility in terms of contributors and topics and aims for an objective tone overall. Where it addresses specific institutions, politics and cultures of learning, it does so primarily to contextualize a specific learning behavior, process, method, theory, or concept.
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.
metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.264
Codex and Gemma teacher scores by category
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.
Teacher spread0.292 · 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
