Reading, Writing, and Presenting Research – Lecture 6

Effective Scientific Communication

  • Four core “F-factors” every piece of scientific communication should satisfy

    • Foundation
    • Think like a scientist → connect to prior empirical work & theory
    • Formulate a clear central research question / thesis before anything else
    • Fidelity
    • Uphold research ethics, methodological rigour, and transparency
    • Be clear, honest, direct; avoid misleading language or visuals
    • Framing
    • Build a strong argument & compelling narrative
    • Organize ideas to maximize audience impact
    • Format
    • Match content to context (journal article, talk, poster, press release, etc.)
    • Adopt appropriate scientific style & tone; respect discipline-specific conventions
  • Competencies effective communicators need

    • Academic writing (journal articles, theses, grant proposals)
    • Talks & posters for conferences
    • Collaborating with peers/colleagues (memos, preregistrations, OSF pages)
    • Explaining work to non-scientists, journalists, policy makers
  • Example of communication failure → misleading COVID-19 cumulative testing bar chart

    • Bars showed ever-increasing total tests; visually implied improving capacity
    • Linearly rising cumulative series actually reflects no improvement in daily testing rate
    • Lesson: design choices can distort interpretation (graphical integrity)

Structure of a Typical Primary-Source Article

  • Abstract – miniature version of the entire paper (objectives, methods, key results, conclusions)

  • Introduction – funnel from broad topic to specific gap; ends with purpose / hypotheses

  • Methods – enough detail to replicate (participants, design, materials, procedure, analyses)

  • Results – objective statistical outcomes without interpretation (tables & figures here)

  • Discussion – interpret results, situate in literature, note limitations, future directions, broad implications

  • Extra front/back matter: title, authors/affiliations, COI & funding statements, data‐availability, reference list

  • Confirmatory vs. Exploratory designs

    • Confirmatory: pre-specified, theory-driven hypotheses, fixed analyses (↑ replicability, ↓ researcher degrees-of-freedom)
    • Exploratory: flexible, pattern-searching, theory-generating but ↑ bias risk

APA Writing

  • Two complementary facets

    • Technical mechanics (APA 7)
    • Headings hierarchy, line spacing, page numbering, font (e.g., 12-pt TNR), indentation
    • Rules for abbreviations, numerals vs. words, punctuation, statistical reporting, citations
    • General scholarly writing skills
    • Continuity & flow, word choice, concision, tone, logical organization
  • APA ≠ only style; e.g., Vancouver style (numeric in-text, biomedical journals)

  • Why learn APA?

    • Required for current assignments, later coursework, theses, manuscripts
    • Emphasises clarity over technical trivia—communication > pedantry

Continuity & Flow

  • Continuity = logical consistency across text; Flow = smooth cadence of sentences
  • Use transitions: time ("after"), cause-effect ("therefore"), addition ("moreover"), contrast ("however")

Concision

  • Remove “weasel” words (really, actually), redundant pairs (hope and trust), obvious fillers (end result), verbose negatives ("not many" → "few")
  • Vary sentence & paragraph length; avoid both run-ons and telegraph style

Tone & Word Choice

  • Direct, professional, engaging
  • Prefer precise verbs (demonstrates vs. suggests vs. implicates)
  • Limit jargon unless essential; translate “therapeutic intervention provider” → “therapist”

Active vs. Passive Voice

  • Active clearer and shorter but passive acceptable when actor unimportant or known, or for stylistic variation
  • Beware using passive merely to hide responsibility

Common Latin Abbreviations (scholarly shorthand)

  • e.g., – for example
  • i.e., – that is / in other words (precise clarification)
  • cf. – compare (to contrast viewpoints)
  • etc. – and so forth (continuing list)

Statistical Reporting Example

  • Proper APA sentence: “There was a statistically significant negative correlation between anxiety symptoms and wellbeing, r = -.53,\; p < .01.”
    • Includes test statistic (r), effect size, p-value, and sign/direction

Key APA-7 Student Paper Formatting Changes

  • No running head; add course name, instructor, due date under title
  • Otherwise keep double spacing, 1-inch margins, page numbers, left-aligned first-line indents

Visualizations

  • Not all visuals are helpful; cluttered “brain infographic” undermines comprehension
  • Figures assist readers when they:
    • Highlight direct comparisons (e.g., Bushman & Gibson 2011 bar plot of experimental conditions)
    • Combine stimuli depiction + results (Taylor et al. 2015) to link task and outcome
    • Clarify complex multi-task methods (Jeon et al. 2012 visual battery)

Principles of Good Data Visualization

  1. Graphical integrity: Represent data honestly (avoid truncated axes, disproportionate shapes)
  2. Match graph type to data & message (see “Which graph should I use?” cheatsheet)
  3. Design for accessibility (color-blind-safe palettes, double encoding by shape & color)
  4. Encourage correct cognitive takeaway; minimize extraneous ink
Classic Demonstrations
  • Anscombe’s quartet: datasets with identical xˉ,  yˉ,  s<em>x,  s</em>y,  r\bar x,\; \bar y,\; s<em>x,\; s</em>y,\; r but radically different scatter patterns → visualize the data!
  • Climate y-axis stretch example: small change magnified to communicate urgency correctly when scale is contextually justified; conversely dishonest when used to exaggerate Obamacare enrollment growth.
  • Scale distortion pitfalls shown with IQ, depression scores, body temperature graphs (truncated axes change perceived differences)
  • Assumed linearity example: plotting pre/post treatment without revealing curvilinear trend misleads
Accessibility Example
  • Scatterplot encoded by both shape & hue; Photoshop simulation of protanopia demonstrates importance of redundant coding
Multiple Interpretations of Same Numbers
  • Forgetting-rate illustration
    • Raw difference: both groups forgot 3030 percentage points
    • Proportional loss: High learners lost 3080=0.375\frac{30}{80}=0.375 vs. Low learners 3070=0.429\frac{30}{70}=0.429
    • Endpoint comparison: High learners still remember more (50 % vs 40 %)
    • Moral: choose metric that aligns with your research question and explain it explicitly
Graph Selection Cheatsheet
  • Line chart → trends over ordered dimension (time, dosage)
  • Bar chart → discrete categories & counts/means
  • Histogram → distribution of continuous variable
  • Scatter plot → bivariate correlation
  • Violin / Box plot → distribution shape & group comparisons
  • Heatmap → matrix of many correlations or intensities
  • Pie chart → parts-of-whole (use sparingly due to angle decoding difficulties)

Posters & Talks (implied under Format)

  • Use same F-factor principles
  • Posters: rely heavily on visuals → keep text minimal, narrative flows left-to-right/top-to-bottom
  • Talks: slide deck should guide, not repeat, spoken narrative; design graphics for viewing distance

Ethical & Philosophical Implications

  • Transparency = moral obligation (show methods, data, analysis decisions)
  • Misleading visuals or opaque prose violate scientific integrity, hinder reproducibility, misinform public

Practical Connections & Resources

  • University of Toronto Writing Centre, OWL Purdue, UTSC TWC handouts (punctuation, active/passive, transitions)
  • Twitter threads (e.g., @callin_bull, @philipcball) illustrate real-world critique of poor visual communication
  • Writing comics (Tom Gauld) remind us that impenetrable language defeats purpose

Assignment Reminder

  • Assignment 1 due TODAY by 11:59 PM (per Announcements slide)