MétaCan
Menu
Back to cohort
Record W2753688628 · doi:10.1093/scipol/scx048

Research in Arabic-speaking countries: Funding competitions, international collaboration, and career incentives

2017· article· en· W2753688628 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.

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.

Bibliographic record

VenueScience and Public Policy · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
FundersScience and Technology Development FundAgence Nationale de la RechercheDefense Advanced Research Projects AgencyInternational Development Research Centre
KeywordsIncentiveQuality (philosophy)Identification (biology)Order (exchange)Public relationsPolitical scienceArabicEconomic growthBusinessEconomicsFinance

Abstract

fetched live from OpenAlex

Morocco, Tunisia, Egypt, Lebanon, Jordan, and Qatar expanded research funds over the past two decades. The use of competitive calls required researchers to prepare and submit proposals for team-based projects or time-limited research units. Identification of national priorities and societal challenges sought to rally research toward real-world problems, while larger grants encouraged a wider range of research activities and greater levels of ambition. Yet, the incentives within hiring organizations still determine how researchers allocate their time and effort, including whether they even seek external funding or collaboration. Selection and evaluation criteria privileged collaboration with distant, scientifically proficient partners abroad, in order to connect with global networks and rise in international rankings of academic quality. Moving forward, countries need to consider how funding opportunities shape the size and organization of distinct research efforts, and which arrangements are best suited to making meaningful progress on different problems of societal and scientific interest.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0030.003
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 head0.096
GPT teacher head0.457
Teacher spread0.361 · 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