frontier research deep techcorpus analysisdh toolingdigital humanitiestext encoding
Complete evaluation framework
What to assess and how to score it
Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.
01
Evaluation factor
Theoretical command
35% weight
Check command of humanities method plus computational theory: TEI P5 encoding decisions, topic modelling assumptions, distant reading critiques, FAIR and Linked Open Data vocabularies such as CIDOC-CRM.
Evidence to listen for
Explains the underlying theory at the level the role demands, and can go a layer deeper when pushed
Knows which results are established and which are contested
Distinguishes their own contribution from the field's
Comfortable saying where the theory runs out
Five-point scoring guide
1
Poor
Recites terminology without understanding; cannot go one layer deeper.
2
Needs Improvement
Surface familiarity; conflates established results with speculation.
3
Satisfactory
Solid grasp of the core theory; thin at the frontier.
4
Very Good
Strong command; separates settled results from open questions.
5
Excellent
Names specific encoding or modelling choices, cites the scholarly debate behind them, and states where quantitative method breaks down interpretively.
02
Evaluation factor
From theory to hardware or code
30% weight
Ask what they built and shipped: digital editions in Omeka or Scalar, IIIF manifests, Python or R pipelines, OCR/HTR workflows in Transkribus, cleaned datasets on GitHub or Zenodo.
Evidence to listen for
Has built, simulated, or run something real, not only published about it
Knows the gap between the idealised model and the actual apparatus or system
Names the practical constraint that dominates in real conditions
Can describe a result that did not match prediction
Five-point scoring guide
1
Poor
Purely theoretical; no contact with implementation.
2
Needs Improvement
Some exposure but unaware of practical constraints.
3
Satisfactory
Has implemented work; understands the main real-world limits.
4
Very Good
Strong practical record; articulate about theory-versus-reality gaps.
5
Excellent
Points to live URLs, repositories with commit history, and documents their own role in code, encoding, or data curation.
03
Evaluation factor
Research judgement
20% weight
Probe how they choose corpora and scope: handling OCR noise, sampling bias in archives, copyright limits, deciding when a research question suits computation at all.
Evidence to listen for
Chooses problems by tractability and value, not novelty alone
Knows when to abandon a line of work
Reads and evaluates others' results critically
Can say what would falsify their own approach
Five-point scoring guide
1
Poor
Chases novelty; no sense of tractability or when to stop.
2
Needs Improvement
Weak problem selection; persists past the point of value.
3
Satisfactory
Reasonable judgement within a defined programme.
4
Very Good
Selects problems well and knows when to abandon a line.
5
Excellent
Describes abandoning or reframing a method after evidence, and explains sampling gaps in the archive rather than glossing over them.
04
Evaluation factor
Explaining it to non-specialists
15% weight
Look for translation work: grant narratives for NEH or AHRC, briefings for librarians and archivists, teaching workshops, public exhibits built from their data.
Evidence to listen for
Explains the work to an engineer, an executive, or a funder without either mystifying or dumbing it down
Writes clearly
Collaborates across disciplines
Makes the case for resources in terms the audience cares about
Five-point scoring guide
1
Poor
Cannot communicate outside their specialism.
2
Needs Improvement
Explanation is either impenetrable or hollow.
3
Satisfactory
Adequate with technical peers; less effective with lay audiences.
4
Very Good
Explains clearly to specialists and non-specialists alike.
5
Excellent
Explains a network graph or model output in plain language to curators and funders, with concrete examples of funded or adopted proposals.
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