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Record W2791174725 · doi:10.1080/17502977.2018.1426383

Adapting Security Sector Reform to Ground-Level Realities: The Transition to a Second-Generation Model

2018· article· en· W2791174725 on OpenAlexaff
Mark Sedra

Bibliographic record

VenueJournal of Intervention and Statebuilding · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsInternational Council for Canadian Studies
Fundersnot available
KeywordsSecurity sector reformBlueprintTechnocracyState (computer science)Political sciencePoliticsProcess (computing)Political economyPublic administrationEconomic systemSociologyEconomicsLawEngineeringComputer science

Abstract

fetched live from OpenAlex

The security sector reform (SSR) model has entered a period of uncertainty and change. Despite being mainstreamed in international development and security policy, SSR has had a meagre record of achievement. SSR analysts, practitioners and policymakers are increasingly speaking of the need to move to a second-generation SSR model. There is a growing belief that SSR in its current form is too utopian, technocratic, state-centric, and donor-driven to succeed. While there is no universally accepted blueprint for second-generation SSR, a number of characteristics have emerged that have begun to define the contours of this alternative vision: less overtly liberal; willing to engage non-state actors, norms and structures; more modest in is objectives and time frames; attuned to the political nature of the process; and bottom-up in its orientation.

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)0.008
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.011
Scholarly communication0.0060.005
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.086
GPT teacher head0.365
Teacher spread0.279 · 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.

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

Citations51
Published2018
Admission routes1
Has abstractyes

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