OER·harvester

Competency catalogue

The 104 active T2.3 competencies: the vocabulary the harvester searches with, the descriptor the alignment reads, and what the alignment found. Compose a harvest →

What the alignment foundHow often each was searched

How many resources the alignment reads as contributing to each competency or developing it: decided at level 2 or 3, or not decided yet and more likely than not to reach 2. 54 competencies have none, 24 one or two. Every figure is a lower bound: on a sample graded on every competency, the map counts 33% of what was graded 2 or 3, and almost nothing of the 5 competencies underlined with dots.

How many times a harvest has searched for each competency, once for each source it asked. 101 competencies have never been searched. A search is not material found: the aligned view says what came of it.

none 1–2 3–9 10–29 30+
never 1–2 3–5 6–11 12+
DDigital 94212203420012149086012303134 GGreen 0000000102000010000100010 RResilience & Entrepreneurial 004000000000000010000120000 TDeep Tech 72643202372825212335201140010

D24 Digital · Knowledge · Advanced

AI Impact Assessment

Evaluate societal, economic, and personal impact of AI

Alignment

3 resources likely to contribute to it or develop it

0 decided at level 2 or 3 · 3 not decided yet, more likely than not

On a graded sample, 8 pairs were graded 2 or 3 for it, and the map counts 1. The figure above is a blind spot of the alignment: the library holds more for it than the map shows.

Retrieval

0 resources harvested by searching its terms

Never searched yet.

Search vocabulary

Domain group
AI impact assessmentsocietal impacteconomic impactpersonal impactalgorithmic impact assessmentsocial consequencestechnology impact

Zenodo and arXiv take the whole group in one query. GitHub takes one phrase at a time and works left to right, stopping once the competency is satisfied — so on that lane this order decides which terms actually run.

Precision warnings
environmental impact

Recorded on a decision, never subtracted from it.

The compiled queries
zenodo ("artificial intelligence" OR "machine learning" OR "generative AI" OR "deep learning" OR "reinforcement learning" OR "large language model" OR "AI") AND ("AI impact assessment" OR "societal impact" OR "economic impact" OR "personal impact" OR "algorithmic impact assessment" OR "social consequences" OR "technology impact")
arxiv (all:"artificial intelligence" OR all:"machine learning" OR all:"generative AI" OR all:"deep learning" OR all:"reinforcement learning" OR all:"large language model") AND (all:"AI impact assessment" OR all:"societal impact" OR all:"economic impact" OR all:"personal impact" OR all:"algorithmic impact assessment" OR all:"social consequences" OR all:"technology impact")
github · term 1 AI "AI impact assessment" in:name,description,readme fork:false archived:false
github · term 2 AI "societal impact" in:name,description,readme fork:false archived:false
github · term 3 AI "economic impact" in:name,description,readme fork:false archived:false
github · term 4 AI "personal impact" in:name,description,readme fork:false archived:false
github · term 5 AI "algorithmic impact assessment" in:name,description,readme fork:false archived:false
github · term 6 AI "social consequences" in:name,description,readme fork:false archived:false
github · term 7 AI "technology impact" in:name,description,readme fork:false archived:false

Profile f757db959c1c89a7

Alignment descriptor draft

Outcomes
  • Can assess the societal, economic and personal effects of an AI system.
  • Can weigh benefits against harms for different groups.
  • Can use or design an impact assessment for an AI application.
Develops it

Material on assessing AI's impact on society, the economy and individuals, with frameworks and cases the learner analyses.

Only mentions it

An opening sentence on how AI is 'transforming society'.

Alignment terms
impact assessmentsocietal impactlabour marketjob displacementdigital dividesocial impact of ai

Read in a resource's text beside the domain group. They are never compiled into a search.

False friends
data protection impact assessmentenvironmental impact

A term found beside one of these is read as another sense of the words, not as this competency.

Neighbours

Descriptor 511411f3b1c5

How a vocabulary becomes a search

Every candidate must match both concept groups in its title, description or keywords before any content is downloaded. Precision warnings are recorded for audit; they never silently cancel positive evidence.

  1. Official name and description
  2. AI/ML terms and domain terms
  3. Zenodo, arXiv and GitHub syntax
  4. Metadata relevance gate
Mandatory AI/ML group
artificial intelligencemachine learninggenerative AIdeep learningreinforcement learninglarge language modelAI

GitHub's repository search takes one phrase at a time. Measured against the live endpoint, a parenthesised OR group returns nothing at all where each term alone returns thousands, and the 256-character limit rejects a long group outright — so that lane issues one query per term and stops as soon as the competency is satisfied.

coverage-vocabulary-1.3.0+sha256:08ad2cd19868 · catalogue sha256:04970bfc77255b1f

What a descriptor is

A descriptor is how the alignment reads a competency: what a learner who has it can do, what a resource has to do to develop it, what only mentions it, the phrases its subject is written in, its false friends, and how to tell it from the competencies that share its words. The definition above it stays the authority.

Every descriptor is a draft until a partner approves it; 0 of 104 are approved. Read the alignment rubric →

competency-descriptors-1.0.0+sha256:3cc741a61ced